Major Regions Of China Research Articles

Monthly Maximum Magnitude Prediction in the North–South Seismic Belt of China Based on Deep Learning

The North–South Seismic Belt is one of the major regions in China where strong earthquakes frequently occur. Predicting the monthly maximum magnitude is of significant importance for proactive seismic hazard defense. This paper uses seismic catalog data from the North–South Seismic Belt since 1970 to calculate and extract multiple seismic parameters. The monthly maximum magnitude is processed using Variational Mode Decomposition (VMD) with sample segmentation to avoid information leakage. The decomposed multiple modal data and seismic parameters together form a new dataset. Based on these datasets, this paper employs four deep learning models and four time windows to predict the monthly maximum magnitude, using prediction accuracy (PA), False Alarm Rate (FAR), and Missed Alarm Rate (MR) as evaluation metrics. It is found that a time window of 12 generally yields better prediction results, with the PA for Ms 5.0–6.0 earthquakes reaching 77.27% and for earthquakes above Ms 6.0 reaching 12.5%. Compared to data not decomposed using VMD, traditional error metrics show only a slight improvement, but the model can better predict short-term trends in magnitude changes.

Nationwide distribution of perfluoroalkyl ether carboxylic acids in Chinese diets: An emerging concern

With the phase-out of perfluorooctanoic acid (PFOA) and its replacement by perfluoroalkyl ether carboxylic acids (PFECAs), there is a potential for increased exposure to various new PFECAs among the general population in China. While there are existing studies on dietary exposure to legacy perfluoroalkyl and polyfluoroalkyl substances (PFASs), research on dietary exposure to PFECAs, especially among the general Chinese populace, remains scarce. In the present study, we investigated the distribution of PFECAs in dietary sources from 33 cities across five major regions in China, along with the associated dietary intake. Analysis indicated that aquatic animal samples contained higher concentrations of legacy PFASs compared to those from terrestrial animals and plants. In contrast, PFECAs were found in higher concentrations in plant and terrestrial animal samples. Notably, hexafluoropropylene oxide dimer (HFPO-DA) was identified as the dominant compound in vegetables, cereals, pork, and mutton across the five regions, suggesting widespread dietary exposure. PFECAs constituted the majority of PFAS intake (57 %), with the estimated daily intake (EDI) of HFPO-DA ranging from 2.33 to 3.96 ng/kg bw/day, which corresponds to 0.78–1.32 times the reference dose (RfD) (3.0 ng/kg bw/day) set by the United States Environmental Protection Agency. Given the ubiquity of HFPO-DA and many other PFECAs in the nationwide diet of China, there is an urgent need for further research into these chemicals to establish relevant safety benchmarks or consumption advisory values for the diet.

Emission Measurements on a Large Sample of Heavy-Duty Diesel Trucks in China by Using Mobile Plume Chasing.

Real-world heavy-duty diesel trucks (HDTs) were found to emit far more excess nitrogen oxides (NOX) and black carbon (BC) pollutants than regulation limits. It is essential to systematically evaluate on-road NOX and BC emission levels for mitigating HDT emissions. This study launched 2109 plume chasing campaigns for NOX and BC emissions of HDTs across several regions in China from 2017 to 2020. It was found that NOX emissions had limited reductions from China III to China V, while BC emissions of HDTs exhibited high reductions with stricter emission standard implementation. This paper showed that previous studies underestimated 18% of NOX emissions in China in 2019 and nearly half of the real-world NOX emissions from HDTs (determined by updating the emission trends of HDTs) exceeded the regulation limits. Furthermore, the ambient temperature was identified as a primary driver of NOX emissions for HDTs, and the low-temperature penalty has caused a 9-29% increase in NOX emissions in winter in major regions of China. These results would provide important data support for the precise control of the NOX and BC emissions from HDTs.

Evaluation of green development in mariculture: The case of Chinese oyster aquaculture

Green development, which is to achieve economic growth and environmental improvement under the principle of harmony between people and nature, has become the mainstream of the world economy, and green development assessment of the industry is becoming increasingly urgent to achieve sustainable development goals. Combining the concept of green development and the characteristics of the mariculture industry, this study establishes a mariculture evaluation system of “yield & area + green economy + green progress”. Firstly, yield and area data are analyzed separately to reflect the green production of mariculture. Secondly, the evaluation index assesses the green growth of the industry in terms of green economy and green progress, the indices are constructed using the calculated relative indicators, weighted using the average of entropy and CRITIC, and the scores are converted into percentages using the efficacy coefficient method. Thirdly, apply the obstacle degree model to analyze the impact of each indicator, so as to identify the key factors affecting the score, and put forward targeted suggestions for improvement. Then, the evaluation system is applied to compare the green development levels of oyster aquaculture in six major regions in China. The results show that the trend of oyster aquaculture areas in China from 2011 to 2020 is largely influenced by local government policies, and the increase in yield has a positive effect in reducing carbon dioxide concentration and purifying seawater quality, but the disposal of waste by-products has become a serious problem for the development of the industry. Fujian has the highest overall evaluation score, benefiting from the largest domestic market share, while other regions have different strengths in terms of aquaculture technology promotion, yield growth, or oyster production levels. The factors that hinder the green development of each region vary, including low economic income, excessive area growth, and industrial inattention. In a word, Chinese oyster aquaculture needs to pay special attention to the problem of high production and low efficiency brought about by rapid expansion.

Patterns and Trends in Pharmacological Treatment for Outpatients with Postherpetic Neuralgia in Six Major Areas of China, 2015–2019

The aim of this study was to assess the patterns and trends of pharmacological treatment for outpatients with postherpetic neuralgia (PHN) in China in the period 2015-2019. Prescription data for outpatients with PHN were extracted from the database of the Hospital Prescription Analysis Program of China according to the inclusion criteria. The trends in yearly prescriptions and corresponding costs were analyzed and stratified by drug class and specific drugs. A total of 19,196 prescriptions from 49 hospitals in 6 major regions of China were included for analysis. The yearly prescriptions increased from 2534 in 2015 to 5676 in 2019 (p = 0.027), and the corresponding expenditures increased from CNY 898,618 in 2015 to CNY 2,466,238 in 2019 (p = 0.027). Gabapentin and pregabalin are the most commonly used drugs for PHN, and more than 30% of these two drugs were combined with mecobalamin. Opioids were the second most frequently prescribed drug class, and oxycodone accounted for the largest share of the cost. Topical drugs and TCAs are rarely used. The frequent use of pregabalin and gabapentin was in accordance with current guidelines; however, the use of oxycodone raised concerns about rationality and economic burden. The results of this study may benefit the allocation of medical resources and management for PHN in China and other countries.

Investigation of Spatiotemporal Variation and Drivers of Aerosol Optical Depth in China from 2010 to 2020

China has experienced rapid economic growth and serious control of aerosol emissions in the past decade. Thus, the spatiotemporal variations and driving factors of aerosol optical depth (AOD) are urgently needed to evaluate the effectiveness of aerosol control activities. The innovation of this study is a detailed spatial and temporal analysis of aerosol pollution in eight major regions of China from 2010 to 2020 using the MERRA-2 AOD reanalysis product and the driving mechanism based on the Granger causality test, sensitivity, and contribution analysis. The results show that the spatial distribution of AOD varied across the areas. Divided by the Hu Line, the AOD values of the Eastern areas were significantly higher than those of the Western areas. The temporal trend in the last eleven years was dominated by a continuous decline and moderate fluctuations at both annual and seasonal scales. The relationship between socioeconomic factors and AOD drivers was more significant in economically developed regions, suggesting that China pays more attention to haze control while developing its economy. The driving relationship between AOD and temperature was weak, while wind speed and relative humidity were more influential. For vegetation factors, Granger effects were mainly observed in the Northeast, Beijing-Tianjin-Hebei, Guangdong, Central China, and Southwest regions. In the Guangdong and Southwest regions, vegetation and economic factors were the more influential drivers. This study provides a scientific basis for the detection of aerosol changes, driving mechanisms and pollution management in China.

Electricity production, power generation structure, and air pollution: A monthly data analysis for 279 cities in China (2015–2019)

Advancing the clean transition of energy structure and reducing air pollution levels are important actions for achieving sustainable urban development. In this study, we analyze the impact of power production and structure on urban air pollution by analyzing the monthly power generation data of 14,570 power plants in 279 prefecture-level cities from January 2015 to December 2019. These data were matched with social, economic, and resource panel data. The study confirmed the positive impact of the increasing proportion of renewable energy on air pollution mitigation, especially when the proportion of renewable power supply exceeds 28.22%. This positive impact has a significant spatial spillover effect, with more air quality improvement seen in East, Central, Southwest, and Northwest China. By designing installation development scenarios for renewable energy, this paper projects the air pollution in major regions of China in 2030. The projection indicates that the PM2.5 concentration in each region could be lower than 35 μg/m3, but the overall proportion of photoelectric and wind power in the primary energy supply remains small. This highlights the need to increase the mitigation of urban air pollution further, by stimulating the innovation of power generation technology, improving power generation efficiency, and encouraging the large-scale development of renewable energy.

Decoupling between Economic Growth and Carbon Emissions: Based on Four Major Regions in China.

This paper constructs a decoupling model for four major economic regions of China, based on the Tapio decoupling index method and VAR model for carbon emissions to compare and measure the impact of decoupling between carbon emissions and economic growth in China during 1997 to 2019. The results show that the degree of decoupling between economic growth and carbon emissions varies among different economic regions, and the decoupling status is better in all regions at the beginning of the 21st century. In general, the decoupling status in the eastern and western regions is more ideal than that in the central and northeastern regions. The impulse response and variance decomposition results show that renewable energy consumption could always reduce the growth of carbon emission intensity, and its effects are most significant in the western region. The above findings help to reveal the link between economic growth, renewable energy consumption and carbon emissions in China in recent years, and how to ensure a stable economic growth in China while increasing the share of clean energy consumption in each region to achieve carbon neutrality.

Measurement of Embodied Carbon Emission of Trade and Responsibility Sharing Mechanism design: A case of Six Central Provinces of China

In the face of the “ 3 0- 6 0” target, the task of carbon emission reduction in China is particularly arduous. Due to factors such as energy resource endowment and economic and industrial structure, there are large spatial differences in carbon emission levels among regions in China. As a representative region of t h e traditional energy industrial structure, the huge energy consumption of the industrial sector in the central region has caused a large amount of carbon emissions. Based on the MRIO model, this paper measures the embodied carbon emissions of trade and the amount of carbon emissions that the regions should bear in 2012 and 2017 for the eight major regions in China. We found that there is large difference in carbon emissions among the eight regions in China, with the central region ranking first in the country, and this difference is also manifested in the provinces of the central region. In addition, under the producer responsibility principle, the problem of carbon leakage between developed and less developed regions is becoming more prominent, with the central and western regions acting as a “ pollution haven” . Further, to rationalize the carbon emission responsibilities of each region, this paper proposes a shared responsibility scheme and compares it with the producer and consumer responsibility systems. This paper is of practical and theoretical reference significance for the scientific delineation of carbon emission reduction responsibilities and the effective promotion of the overall carbon peaking goal.

Spatial Differentiation of the Coupling Characteristics of Soil Carbon and Nitrogen on Mulberry Plantations in China

Soil is the most important carbon pool of the mulberry plantation ecosystem, so understanding the characteristics of the soil carbon pool in mulberry plantations provides an important basis for the research of carbon sinks in economic forest ecosystems and farmland ecosystems. In order to explore the spatial differentiation pattern of the relationship between carbon and nitrogen in mulberry plantation soil, this study analyzed the organic carbon content and total nitrogen content of the surface soil layer (0–20 cm) and the subsurface soil layer (20–40 cm) of 475 mulberry plantations in five major regions of China, Southwest China (SWC), Central South China (CSC), East China (EC), North China (NC), and Northwest China (NWC). The research showed seven key aspects of this system. (1) The soil organic carbon of mulberry plantations was significantly different at the two soil depths. The average content of organic carbon in the surface layer of mulberry plantation soil was 10.71±7.01g kg–1, which was 37.13% higher than that of the subsurface layer. (2) The soil organic carbon of mulberry plantations had significant differences in spatial differentiation, which was manifested as SWC>CSC>EC>NC>NWC. (3) The total nitrogen content in mulberry plantation soil had significant responses to the region, the soil layer depth, and the interaction between the region and soil layer depth. Among the regions, NWC had no significant difference between the surface layer and subsurface layer of the soil. EC had the maximum difference in total nitrogen content, with the total nitrogen content in the surface soil layer being 56.68% higher than that of the subsurface soil layer. The total nitrogen contents of the surface soil layers in the SWC and NC were 34.27% and 20.79% higher than those of the respective subsurface soil layers. (4) The mulberry plantation soil C/N ratios had a significant response to regional differences, as NWC>SWC> EC>CSC>NC, but this ratio had no significant response to soil depth. (5) Soil pH had significant spatial differentiation in relation to soil organic carbon and total nitrogen content in mulberry plantations. NWC had no significant correlation between pH and organic carbon or total nitrogen content, while CSC had a significant positive correlation between pH and both soil organic carbon and total nitrogen content. Other regions showed significant negative correlations between pH and both organic carbon and total nitrogen content. (6) There was a significant negative correlation between the C/N ratio of the surface soil layer and pH in mulberry plantations, which was mainly contributed by SWC, while the other regions' surface soil layers had no significant correlations between C/N ratio and pH. (7) There was no significant correlation between the C/N ratio and pH in the subsurface soil layer in mulberry plantations. These results reveal that in either the research on mulberry plantation carbon pools or the innovation of green and low-carbon planting technology in mulberry plantations, the spatial differentiation characteristics of soil must be considered. Furthermore, the spatial differentiation of soil organic carbon can be used as the basic foundation for the planning and design of mulberry afforestation or ecological restoration projects.

Variations of the urban PM2.5 chemical components and corresponding light extinction for three heating seasons in the Guanzhong Plain, China

In order to investigate the variations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) chemical components responding to the pollution control strategy and their effect on light extinction (bext) in the Guanzhong Plain (GZP), the comparisons of urban atmospheric chemical components during the heating seasons were extensively conducted for three years. The average concentration of PM2.5 decreased significantly from 117.9 ± 57.3 μg m−3 in the heating season 1 (HS1) to 53.5 ± 31.3 μg m−3 in the heating season 3 (HS3), which implied that the effective strategies were implemented in recent years. The greatest contribution to PM2.5 (∼30%) was from Organic matter (OM). The heightened contributions of the secondary inorganic ions (SNA, including NO3−, SO42−, and NH4+) to PM2.5 were observed with the values of 34% (HS1), 41% (HS2), and 42% (HS3), respectively. The increased percentages of NO3− contributions indicated that the emission of NOx should be received special attention in the GZP. The comparison of PM2.5 chemical compositions and implications across major regions of China and the globe were investigated. NH4NO3 was the most important contributor to bext in three heating seasons. The average bext was decreased from 694.3 ± 399.1 Mm−1 (HS1) to 359.3 ± 202.3 Mm−1 (HS3). PM2.5 had a threshold concentration of 75 μg m−3, 64 μg m−3, and 57 μg m−3 corresponding to the visual range (VR) < 10 km in HS1, HS2, and HS3, respectively. The enhanced impacts of the oxidant on PM2.5 and O3 were observed based on the long-term variations in PM2.5 and OX (Oxidant, the sum of O3 and NO2 mixing ratios) over the five heating seasons and PM2.5 and O3 over six summers from 2016 to 2021. The importance of coordinated control of PM2.5 and O3 was also investigated in the GZP.

A Development of Green Finance and Regional Eco-Efficiency in China

Based on panel data collected from 30 Chinese provinces between 2009 and 2020, we used the Super-SBM model to calculate regional eco-efficiency (EE) and analyze its spatial–temporal evolution characteristics. Furthermore, we constructed SDM to analyze the direct impact and spillover effect and tested its mechanism with a mediating effects model. According to the SDM results, it is confirmed that both the direct impact of green financial development on regional eco-efficiency improvement and the spatial spillover effects on neighboring provinces have a “U” shaped relationship, and there is significant heterogeneity among the three major regions of China (East, Central, and West). The intermediary effect model found an asset scale and technological progress effect. Based on the findings of the study, policy implications are proposed to expand the scale of green finance, promote its coordinated regional development, promote technological progress and expand the scale of capital.

Does Technological Innovation Curb O3 Pollution? Evidence from Three Major Regions in China.

At the end of 2020, when China’s three-year Blue Sky Protection Campaign was successfully concluded, the main pollutants, led by O3, increased instead of decreasing, creating a new air pollution problem. In this paper, the impact of the technological innovation level on O3 pollution and its inter-regional differences across three major regions from 2014 to 2019 are studied using the dynamic spatial Durbin model. Generally, in terms of ozone pollution showing significant spatial correlation, technological innovations in China are still not effective in curbing ozone pollution. Furthermore, technological innovation is a key factor affecting ozone pollution, and it is heterogeneous, demonstrating that the impact of technological innovation on O3 pollution is different among regions. Technological innovation in Beijing–Tianjin–Hebei significantly reduces local O3 pollution with spillover, while technological innovation in the Yangtze River Delta instead significantly exacerbates local O3 pollution, and the impact of technological innovation on O3 pollution in the Fenwei Plain is not significant. Third, other factors in O3 pollution also differ between regions, with the number of cars and the amount of foreign capital actually utilized being the main factors. Therefore, we should pay attention to the spillover of O3 pollution and technological innovation and strengthen regional cooperation according to our own characteristics to effectively suppress O3 pollution. Finally, the findings of this paper are representative, which provides a possible reference for other similar national or regional studies.

Evaluation of Long-Term Modeling Fine Particulate Matter and Ozone in China During 2013–2019

Air quality in China has been undergoing significant changes due to the implementation of extensive emission control measures since 2013. Many observational and modeling studies investigated the formation mechanisms of fine particulate matter (PM2.5) and ozone (O3) pollution in the major regions of China. To improve understanding of the driving forces for the changes in PM2.5 and O3 in China, a nationwide air quality modeling study was conducted from 2013 to 2019 using the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. In this study, the model predictions were evaluated using the observation data for the key pollutants including O3, sulfur dioxide (SO2), nitrogen dioxide (NO2), and PM2.5 and its major components. The evaluation mainly focused on five major regions, that is , the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), the Chengyu Basin (CY), and the Fenwei Plain (FW). The CMAQ model successfully reproduced the air pollutants in all the regions with model performance indices meeting the suggested benchmarks. However, over-prediction of PM2.5 was noted in CY. NO2, O3, and PM2.5 were well simulated in the north compared to the south. Nitrate (NO3−) and ammonium (NH4+) were the most important PM2.5 components in heavily polluted regions. For the performance on different pollution levels, the model generally over-predicted the clean days but underpredicted the polluted days. O3 was found increasing each year, while other pollutants gradually reduced during 2013–2019 across the five regions. In all of the regions except PRD (all seasons) and YRD (spring and summer), the correlations between PM2.5 and O3 were negative during all four seasons. Low-to-medium correlations were noted between the simulated PM2.5 and NO2, while strong and positive correlations were established between PM2.5 and SO2 during all four seasons across the five regions. This study validates the ability of the CMAQ model in simulating air pollution in China over a long period and provides insights for designing effective emission control strategies across China.

A Summary of the Analysis of the Problems Existing in the Development of Asset Appraisal Industry in Western China

Affected by the development level of the market economy and regional economic growth factors, the asset appraisal industry in the three major regions of China's east, middle and west has created regional gaps in the development process. Among them, the asset appraisal development problem in the western region is particularly prominent. Therefore, the development of asset appraisal in the western region has always been a hot topic in this field. This paper compares the economic development level of various regions and the development status of the asset appraisal industry, analyzes the problems encountered in the development of the asset appraisal industry in the western region, considers solutions to related problems, and further thinks about the future development direction of the asset appraisal industry and outlook.

Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model

Green innovation is an important capability for an enterprise’s sustainable development. Evaluating the green innovation efficiency of China’s industrial enterprises can greatly affect its improvement. Considering the existing research results of green innovation efficiency evaluation, this paper added the impact of environmental factors in the technology industrialization stage. Various negative environmental externality indicators produced by industrial enterprise activities were incorporated into the undesired output, and an index system and model were constructed for evaluating the green innovation efficiency of China’s industrial enterprises. Combined with the actual data, a three-stage chain network SBM (slack-based measure) model was used to dynamically evaluate and analyze the industrial enterprises in 29 Chinese provinces. The results show that the overall efficiency of green innovation in China’s industrial enterprises has an upward trend, and the rise fluctuates during the technological development, achievement transformation, and industrialization stages. In the three major regions of China, industrial enterprises in the eastern area have the highest green innovation efficiency, and the industrial enterprises in the west and central regions have lower efficiencies. Based on the evaluation results, the corresponding countermeasures are proposed.

Energy consumption, CO2 emissions, and agricultural disaster efficiency evaluation of China based on the two-stage dynamic DEA method.

With a large agricultural sector, China is greatly affected by natural disasters caused by extreme weather events. Because the occurrence of natural disasters is closely related to the sharp increased consumption of energy and the massive emissions of carbon dioxide, this research examines relevant data from 2013 to 2017 in four major regions of China that cover 30 provincial administrative regions. Using the two-stage dynamic DEA model, we evaluate total efficiency value, two-stage efficiency value, and the efficiencies of energy consumption, CO2 emissions, and crop disaster areas, setting CO2 as the link between the production stage (first stage) and the crop damage stage (second stage). The research findings show that overall efficiency in China is generally low, whereby the total efficiencies of eastern and northeastern China are higher than those of central and western China. The efficiency value of the first stage (production stage) is greater than that of the second stage (crop damage stage), and the efficiency of most administrative regions' second stage is below 0.3, which is the main reason for the country's low overall efficiency. There is little difference between China's CO2 and energy consumption efficiency scores, but the efficiency values of crop disaster areas fluctuate greatly. The efficiency scores of various indicators in the eastern region are generally higher and more balanced, and the total efficiency scores exhibit a decreasing trend from east to west. Therefore, it is necessary to implement the environmental policy of controlling energy consumption and early warning of natural disasters in the central and western regions, and promote the R&D industry and technological innovation of carbon dioxide emission reduction and disaster control in the economically developed eastern regions.

Impact of Healthcare-Associated Infections on Length of Stay: A Study in 68 Hospitals in China.

Healthcare-associated infections (HAIs) not only bring additional medical cost to the patients but also prolong the length of stay (LOS). 2119 HAI case-patients and 2119 matched control-patients were identified in 68 hospitals in 14 primary sampling provinces of 7 major regions of China. The HAI caused an increase in stay of 10.4 days. The LOS due to HAI increased from 9.7 to 10.9 days in different levels of hospitals. There was no statistically significant difference in the increased LOS between different hospital levels. The increased LOS due to HAI in different regions was 8.2 to 12.6 days. Comparing between regions, we found that the increased LOS due to HAI in South China is longer than other regions except the Northeast. The gastrointestinal infection (GI) caused the shortest extra LOS of 6.7 days while the BSI caused the longest extra LOS of 12.8 days. The increased LOS for GI was significantly shorter than that of other sites. Among 2119 case-patients, the non-multidrug-resistant pathogens were detected in 365 cases. The average increased LOS due to these bacterial infections was 12.2 days. E. coli infection caused significantly shorter LOS. The studied MDROs, namely, MRSA, VRE, ESBLs-E. coli, ESBLs-KP, CR-E. coli, CR-KP, CR-AB, and CR-PA were detected in 381 cases (18.0%). The average increased LOS due to these MDRO infections was 14 days. Comparing between different MDRO infections, we found that the increased LOS due to HAI caused by CR-PA (26.5 days) is longer than other MDRO infections (shorter than 19.8 days).

Urban Land Intensive Use Evaluation Study Based on Nighttime Light—A Case Study of the Yangtze River Economic Belt

Urban land intensive use meets the requirements for the sustainable development of urban land and is an important part of urban sustainable development. The Yangtze River Economic Belt (YREB) spans the three major regions of China, which are the most active areas of China’s economy. The contradiction between humans and land is becoming more acute. There are also regional differences in land use patterns affecting the coordinated development of the YREB and the construction of an ecological civilization. Therefore, the scientific evaluation of urban land intensive use is a key area in the current research field of urban sustainable development. In this study, the YREB is chosen as the research object, and urban land intensive use is studied using nighttime light data and statistical data on the urban built-up area. An evaluation model based on urban nighttime light intensity and land urbanization is constructed with an allometric growth model. Considering that the impact of land urbanization on urban nighttime light has a possible lag effect, an evaluation model of land intensive use that considers the lag effect between urban nighttime light and the land urbanization level is proposed. Using urban agglomerations and some typical cities in the study area as research samples, the characteristics of urban nighttime light and land urbanization are analyzed to reveal the spatial and temporal characteristics of land development in the YREB. The results show that nighttime light remote-sensing data can better reflect the level of urban land use, the allometric growth model can better fit the intensity of urban light and the land urbanization level, and the allometric growth characteristics can reflect the land use characteristics of different cities and urban agglomerations. In regional experiments with typical cities and with urban agglomerations, compared to the original allometric growth model, the goodness of fit of the allometric growth model with the lag effect improves, on average, by 3.2% and 2%, respectively, with the highest increases being by 9.9% and 4.9%, respectively. The level of intensive land use in the YREB gradually decreases from east to west, and there are great differences among different cities in the provinces and urban agglomerations. The lower reaches of the Yangtze River have high land intensive use on the whole. In the middle reaches, multicenter cities have a greater efficiency of land use than the surrounding cities. In the upper reaches, only Chengdu and Chongqing have clear advantages in urban land intensive use. The results of this study can be helpful in providing an important reference for the sustainable development of land in the YREB and can provide a basis for future urban land optimization and sustainable development. Realizing the coordination and linkage between key cities and major cities is the key to enhancing the overall sustainable development ability of the core cities in the YREB.

Revealing the regional distribution of soybean lunasin content in China and the effects of climate factors by sampling extensively.

Lunasin is a novel therapeutic peptide that was initially isolated from soybean. In this study, we quantified the variations in lunasin content in a total of 413 soybean samples that were collected from four major regions in China and harvested in 2014 and 2015 to reveal the regional distribution of soybean lunasin content in China and the effects of climate factors. The results showed that the cultivar Changmidou 30 collected from Jilin province and harvested in 2015 had the highest lunasin content (3.25 g kg-1 dry seeds). The data from both 2014 and 2015 showed that the lunasin content in soybean collected from northern China was significantly higher (P<0.05) than that from south China. There was a positive correlation (P<0.01) between lunasin content and hours of sunshine (HS) as well as diurnal temperature range (DTR); however, there was a negative correlation (P<0.01) between lunasin content and rainfall (RF). In addition, combined analysis of data from 2014 and 2015 demonstrated that DTR was the dominant factor that affected lunasin content with a direct path-coefficient of 0.301. These results were anticipated to contribute to guiding the cultivation of soybean with high lunasin content. © 2018 Society of Chemical Industry.