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Background: Shexian Dryland Stone Terraced System (SDSTS) in the Taihang Mountains was formally recognized as Globally Important Agricultural Heritage Systems (GIAHS) by Food and Agriculture Organization on May 20, 2022. People there have been relying on the terraced fields for centuries, using various plants, including medicinal plants. However, little information was reported about the flora in SDSTS, nor medicinal plants. Thus, the present study aims to identify and document medicinal plants traditionally used by the local people living around the SDSTS and associated ethnobotanical knowledge. Methods: We conducted investigations in Shexian County, Hebei Province, North China, where SDSTS is distributed. Then, Wangjinzhuang, a community located in the core zone of SDSTS, was chosen as the case site. We selected the informants through purposive and snowball sampling. The data were collected through semi-structured interviews, participant observation, and key informant interviews. The medicinal plants traditionally used by the local people were documented and analyzed. We examined and confirmed the botanical identification based on voucher specimens and by cross-checking the descriptions with the series of books, scientific papers on medicinal plants, and the plant databases. Results: The local people have rich traditional knowledge to collect and use medicinal plants in SDSTS. Records of 123 medicinal plant species belonging to 51 families were obtained from SDSTS. Asteraceae was represented by 16 species, followed by Fabaceae, Lamiaceae and Ranunculaceae. (They all have 8 species.) The majority of the reported plant species were commonly processed into decoctions. And 180 diseases affecting humans were reported to be treated with traditional medicinal plants from SDSTS. Conclusion: It is the first ethnobotanical study on medicinal plants in China-Nationally Important Agricultural Heritage Systems, and in globally important agricultural heritage systems as well. Medicinal plants are crucial for people living in Shexian County. It is necessary to recognize and respect traditional knowledge peculiar to the mountainous region of northern China, especially for those involved in the human–nature interaction and the role of knowledge in agrobiodiversity conservation and rural development that local residents have persisted for centuries. [ABSTRACT FROM AUTHOR]

Landslide dams are caused by landslide materials blocking rivers. After the occurrence of large-scale landslides, it is necessary to conduct large-scale investigation of barrier lakes and rapid risk assessment. Remote sensing is an important means to achieve this goal. However, at present remote sensing is only used for monitoring and extraction of hydrological parameters at present, without prediction on potential hazard of the landslide dam. The key parameters of the barrier dam, such as the dam height and the maximum volume, still need to be obtained based on field investigation, which is time-consuming. Our research proposes a procedure that is able to calculate the height of the landslide dam and the maximum volume of the barrier lake, using single remote sensing image and pre-landslide DEM. The procedure includes four modules: (a) determining the elevation of the lake level, (b) determining the elevation of the bottom of the dam, (c) calculating the highest height of the dam, (d) predicting the lowest crest height of the dam and the maximum volume. Finally, the sensitivity analysis of the parameters during the procedure and the analysis of the influence of different resolution images is carried out. This procedure is demonstrated through Baige Landslide Dam in south-west China. The single image from Beijing-1 and pre-landslide DEM, SRTM V3, are used to predict the height of the dam and the key parameters of the dam break, which are in good agreement with the measured data. This procedure can effectively support the quick decision-making regarding hazard mitigation. [ABSTRACT FROM AUTHOR]

The probability distributions of hydrological series are primarily determined according to the best fitting of empirical probability from observation data. The fitted distribution functions are variable in different watersheds, and thus difficult to be applied to estimate probability of any discharge occurrence at other stations. In this study, chaotic characteristics of annual discharge series are analyzed by using correlation dimension analysis at 12 hydrological stations in the six main rivers in China. It is found that the correlation integral of annual discharge series represents the probability distribution of difference between any two annual discharges. The derived probability function can be perfectly fitted by the Pearson III function. Although the six basins have distinctively different climate conditions from the northern cold temperature zone to the southern subtropical zone, the correlation dimension of chaotic characteristics for annual discharges are similar at the 12 hydrological stations. The mean of difference between any two annual discharges, the maximum and minimum of annual discharge are found to be high correlation with the mean of annual discharge. Moreover, the derived probability distributions at 12 hydrological stations can be normalized by a universal distribution function, and the derived probability is high correlation with the probability distribution of annual discharge. This universal probability distribution can be easily applied to obtain probability distributions of annual discharge series over any stations. [ABSTRACT FROM AUTHOR]

The accurate extraction of burned area is important for biomass burning monitoring and loss evaluation. Environment and Disasters Monitoring Microsatellite Constellation put forward by China has two satellites of HJ-1A and HJ-1B in orbit. Each satellite has two CCD cameras with four bands to meet the need of mapping burned area. In order to evaluate the capability for mapping the burned area using HJ satellite's CCD data, a forest fire occurring in Yuxi, Yunnan Province of Southwest China, was selected to analyze the spectral characteristic in the range of visible and near infrared in this paper. The research of mapping burned area was carried out based on the HJ satellites using three spectral indices (NDVI, GEMI and BAI). The color composite images including NIR band could reflect the spectral change in post-fire vegetation with a higher repetition cycle (2 days, or 1 day in some region) and higher spatial resolution (30 m). Through the comparison with the discrimination index M and extraction accuracy, the BAI has higher discrimination capability than NDVI and GEMI, and the highest M value is 2.1943. The extraction of burned area based on BAI showed higher accuracy, and the highest kappa value is 0.8957. Using HJ satellites, the map of burned area with higher temporal-spatial resolution and higher accuracy could provide the potential for dynamic monitoring and analyzing fire behavior. [ABSTRACT FROM AUTHOR]

Water rights management modeling was considered the useful measure to ensure efficient water resources allocation and to avoid intensifying conflicts over water rights. Regarding to the two major patterns of water rights across the world, namely, quantitative water rights (QWR) and duration-based water rights (DWR), the corresponding measures are fastidious. Since QWR was established to set water entitlements instead of DWR in Heihe River Basin, China, the disability of usual DWR tool, managing water diversion by water intakes closing (WIC) during a certain period, has arisen increasingly. The historical data also reflected the low reliability of DWR in allocating water resources quantitatively without modeling guidelines. Aimed at the challenge, a modeling framework and a mixed integer optimization model (MIOM) combing QWR objectives and DWR tools were developed, by which the optimal schemes in Pareto frontier were found to improve the water intake on/off events, including WIC stages, duration days, and starting date through long term series probability analysis and historical data. Results showed that the reliability of DWR allocation was enhanced and WIC duration was reduced significantly compared with current regulation. Scenario analyses indicated that MIOM was powerful for assisting DWR tool to manage QWR and the proposed framework was able to manage water rights efficiently in comparable basins. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas contributing to global climate change. SCIAMACHY on board ENVISAT (launched in 2002) is the first satellite instrument to monitor the changes in CO2 concentration in the lowest atmospheric layers. The temporal and spatial distribution of CO2 (2003–2009) concentration based on SCIAMACHY over China is presented and discussed. It shows an annual increase and a seasonal cycle. The CO2 annual growth rate was about 1.8 ppm year−1, with the highest value being in spring and the lowest in autumn. The CO2 concentration variation is determined by many complex factors. In this article, we analyse the important factors affecting CO2 variations, with special emphasis on terrestrial ecosystems and energy consumption. Terrestrial ecosystems are an important sink in the global carbon cycle. The relationship between CO2 concentration and Moderate Resolution Imaging Spectroradiometer (MODIS) net primary production (NPP) in 2008 is analysed. CO2 concentration is inversely proportional to NPP both in regions with high-density vegetation and in deserts. The Yunnan province has the highest NPP value and the lowest CO2 concentration, whereas the Takla Makan Desert has the lowest NPP value and the highest CO2 concentration. Energy consumption is the main emission source of atmospheric CO2. CO2 emissions from energy consumption show a steady increase in China since 1980. China's CO2 concentration variation shows a high correlation with energy consumption (coefficient of determination (R 2) > 0.8). The regions with high energy consumption are major industrial regions such as Shandong, Guangdong, Jiangsu, Zhejiang, Hebei, and Henan. [ABSTRACT FROM PUBLISHER]

• NG and COG consumption is computed based on BF mass and heat balance and simulated. • The raceway state is compared as the coal ratio is same and NG and COG are used. • NG injection has more effect on coal reaction behaviors compared with COG. The application of hydrogen-rich gas in the pulverized coal injection technology represents a precious solution to mitigate carbon emissions. In this research, a three-dimensional physical model has been constructed based on the actual dimensions of the gas lance, coal lance, blowpipe, tuyere and raceway of a prominent blast furnace in China. A comparative analysis of the tuyere and raceway status, along with the coal combustion behaviors, is conducted using numerical simulation method after the injection volume of the two hydrogen-rich gases changes. The simulation outcomes demonstrate that the introduction of natural gas into the blast furnace has a comparatively larger influence on the temperature within the raceway, in contrast to the injection of coke oven gas, leading to a more noticeable temperature reduction. Additionally, the average temperature at the tuyere outlet is about 20 K higher with coke oven gas injection compared to natural gas injection under equivalent coal ratios. Furthermore, the burnout of particles is lower in the case of natural gas injection compared to coke oven gas injection. When the injection rates of natural gas and coke oven gas increase, and the coal ratio decreases from 170 kg/t to 140 kg/t, the burnout of coal powder decreases from 68.11% to 64.12% and 64.73%, respectively. The impact of injecting natural gas on coal powder combustion is more pronounced. The research offers a theoretical guide for advancing the mixed application of natural gas, coke oven gas, and particles in the blast furnace, serving as a valuable guide for practical implementation. [ABSTRACT FROM AUTHOR]

Knowledge of the spatial distribution of populations at finer spatial scales is of significant value and fundamental to many applications such as environmental change, urbanization, regional planning, public health, and disaster management. However, detailed assessment of the population distribution data of countries that have large populations (such as China) and significant variation in distribution requires improved data processing methods and spatialization models. This paper described the construction of a novel population spatialization method by combining land use/cover data and night-light data. Based on the analysis of data characteristics, the method used partial correlation analysis and geographically weighted regression to improve the distribution accuracy and reduce regional errors. China's census data for the years 1990, 2000, and 2010 were assessed. The results showed that the method was better at population spatialization than methods that use only night-light data or land use/cover data and global linear regression. Evaluation of overall accuracies revealed that the coefficient of correlation R-square was >0.90 and increased by >0.13 in the years 1990, 2000, and 2010. Moreover, the local R-square of over 90% of the samples (counties) was higher than the adjusted R-square of the general linear regression model. Furthermore, the gridded population density datasets obtained by this method can be used to analyse spatial-temporal patterns of population density and provide population distribution information with increased accuracy and precision compared to conventional models. [ABSTRACT FROM AUTHOR]

The Three-River Headwaters (TRH) region in the Qinghai-Tibet Plateau, China, is of key importance to the ecological security of China and Southeast Asia and contains some of the most sensitive and fragile ecosystems. Monitoring and evaluating the ecosystem service function and its changes in the TRH region could support decision-making for regional ecological protection and restoration programs. Referencing the concept of ecosystem service and the Millennium Ecosystem Assessment (MA) framework, this study built a system of indicators for monitoring and evaluating the ecosystem service function. Thus, combining a multicriteria decision analysis (MCDA) and weighted linear combination (WLC) with analytic hierarchy process (AHP), we applied the ecosystem service function index (ESFI) based on remote sensing data at 1-km spatial resolution to spatiotemporally monitor the changes during the period 2005-2010. The study results indicated that ESFI had a good performance for monitoring the ecosystem service function and showed an improving trend in the TRH region over the past 5 years. Ecosystem environment recovery not only reflected the changing trend of warm and wet climate but was also a response of the ecological protection project of the Key Ecological Function Zone in the TRH region.

Giardia duodenalis is a common and widespread intestinal protozoan parasite of both humans and animals. Previous epidemiological and molecular studies have identified Giardia infections in different animals and humans, but only limited information is available about the occurrence and genotypes of Giardia in cattle in China. In this study, we determined the occurrence of giardiasis and genetically characterized G. duodenalis in dairy cattle in Henan Province, central China. The overall prevalence of G. duodenalis was 7.2% (128/1777) on microscopic analysis, with the highest infection rate (22.7%) in calves aged less than 1 month. G. duodenalis assemblages and subtypes were identified with multilocus genotyping based on the SSU rRNA, β-giardin (bg), glutamate dehydrogenase (gdh), and triosephosphate isomerase (tpi) genes. Two assemblages were detected in the successfully sequenced samples: assemblage A (n = 58), assemblage E (n = 21), with a mixed E and A assemblage (n = 2). Four novel subtypes of the gdh gene and seven of the bg gene were found among the G. duodenalis assemblage E isolates. Using the nomenclature for the multilocus genotype (MLG) model, nine novel multilocus genotypes E (MLGs E1-E9) and three MLGs A (a novel subtype AI, previously detected subtype AII-1, and a combination of both) were identified. MLG AII-1 identified in this study may be an important zoonotic subtype. The dairy cattle in Henan are a potential public health concern.