6 research outputs found

    Ecological Wisdom and Inheritance Thinking of the Traditional Village’s Water Resources Management in Taihang Mountains

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    In the context of China’s rapid urbanization, the landscape texture and ecosystem of traditional villages are being constructively damaged, especially the water ecosystem responsible for maintaining the sustainable development of villages. It is urgent to explore the green construction technology of traditional villages. However, some traditional villages in Taihang Mountain area exist and develop in the environment of drought and flood, which contains rich ecological water resources management wisdom. Therefore, in this paper, Taihang Mountain is selected as the research area to collect data through literature analysis, field research, and in-depth interviews. This study uses ArcGIS spatial analysis and statistical functions to analyze the acquired data and explore the water resources management practices of traditional villages based on three aspects: safety, function, and spirit. Then it summarizes four key inspirations for contemporary water resources management: “adapt to local conditions, pay equal attention to water use and prevention”; “division of labor and cooperation complement each other”, “low cost, low technology, low maintenance” and “make the best use of materials and compound functions”. These advantageous insights can be offered for the preservation of traditional villages, the enhancement of the living environment, and the management and growth of urban stormwater

    Association between Perfluoroalkyl and Polyfluoroalkyl Substances and Women’s Infertility, NHANES 2013–2016

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    Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are widely used in consumer products. However, the role of PFAS in infertility is still poorly understood. A total of 788 women from the 2013–2016 nationally representative NHANES were included to explore the association between PFAS exposure and self-reported infertility. Six PFAS, including PFDE, PFNA, PFHxS, n-PFOA, n-PFOS, and Sm-PFOS, were detected by online SPE-HPLC-TIS-MS/MS. We used the generalized linear regression model (GLM), generalized additive models (GAM), and Bayesian kernel machine regression (BKMR) to assess the single effects, non-linear relationships, and mixed effects on women’s infertility, respectively. The prevalence of self-reported infertility was 15.54% in this study. In GLM, n-PFOA showed a negative association with self-reported infertility in women for the Q3 (OR: 0.396, 95% CI: 0.119, 0.788) and Q4 (OR: 0.380, 95% CI: 0.172–0.842) compared with Q1 (p for trend = 0.013). A negative trend was also observed in n-PFOS and ∑PFOS (p for trend < 0.05). In GAM, a non-linear relationship was revealed in Sm-PFOS, which exhibits a U-shaped relationship. The BKMR model indicated that there might be a joint effect between PFAS and women’s infertility, to which PFNA contributed the highest effect (PIP = 0.435). Moreover, age stratification analysis showed a different dose–response curve in under and above 35 years old. Women under the age of 35 have a more noticeable U-shaped relationship with infertility. Therefore, the relatively low level of mixed PFAS exposure was negatively associated with self-reported infertility in women in general, and the impact of PFAS on infertility may vary among women of different age groups. Further studies are needed to determine the etiological relationship

    Receptivity to malaria in the China–Myanmar border in Yingjiang County, Yunnan Province, China

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    Abstract Background The re-establishment of malaria has become an important public health issue in and out of China, and receptivity to this disease is key to its re-emergence. Yingjiang is one of the few counties with locally acquired malaria cases in the China–Myanmar border in China. This study aimed to understand receptivity to malaria in Yingjiang County, China, from June to October 2016. Methods Light-traps were employed to capture the mosquitoes in 17 villages in eight towns which were categorized into four elevation levels: level 1, 0–599 m; level 2, 600–1199 m; level 3, 1200–1799 m; and level 4, > 1800 m. Species richness, diversity, dominance and evenness were used to picture the community structure. Similarity in species composition was compared between different elevation levels. Data of seasonal abundance of mosquitoes, human biting rate, density of light-trap-captured adult mosquitoes and larvae, parous rate, and height distribution (density) of Anopheles minimus and Anopheles sinensis were collected in two towns (Na Bang and Ping Yuan) each month from June to October, 2016. Results Over the study period, 10,053 Anopheles mosquitoes were collected from the eight towns, and 15 Anopheles species were identified, the most-common of which were An. sinensis (75.4%), Anopheles kunmingensis (15.6%), and An. minimus (3.5%). Anopheles minimus was the major malaria vector in low-elevation areas (< 600 m, i.e., Na Bang town), and An. sinensis in medium-elevation areas (600–1200 m, i.e., Ping Yuan town). In Na Bang, the peak human-biting rate of An. minimus at the inner and outer sites of the village occurred in June and August 2016, with 5/bait/night and 15/bait/night, respectively. In Ping Yuan, the peak human-biting rate of An. sinensis was in August, with 9/bait/night at the inner site and 21/bait/night at the outer site. The two towns exhibited seasonal abundance with high density of the two adult vectors: The peak density of An. minimus was in June and that of An. sinensis was in August. Meanwhile, the peak larval density of An. minimus was in July, but that of An. sinensis decreased during the investigation season; the slightly acidic water suited the growth of these vectors. The parous rates of An. sinensis and An. minimus were 90.46 and 93.33%, respectively. Conclusions The Anopheles community was spread across different elevation levels. Its structure was complex and stable during the entire epidemic season in low-elevation areas at the border. The high human-biting rates, adult and larval densities, and parous rates of the two Anopheles vectors reveal an exceedingly high receptivity to malaria in the China–Myanmar border in Yingjiang County

    C-band Scatterometer (CScat): the first global long-term satellite radar backscatter data set with a C-band signal dynamic

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    International audienceAbstract. Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness, and can be acquired in all weather conditions, thus has been used in a range of earth science disciplines. However, there is no single global radar data set that spans more than two decades. This has limited the use of radar data for trend analysis over extended time intervals. We here provide the first long-term (since 1992), high resolution (~8.9 km) satellite radar backscatter data set over global land areas, the C-band Scatterometer (CScat) data set, by fusing signals from European Remote Sensing satellite (ERS, 1992–2001, C-band, 5.3 GHz), Quick Scatterometer (QSCAT, 1999–2009, Ku-band, 13.4 GHz), and the Advanced Scatterometer (ASCAT, since 2007, C-band, 5.255 GHz). The six-year data gap between C-band ERS and ASCAT was filled out by modelling an equivalent C-band signal during 1999–2009 from Ku-band QSCAT signals and climatic information. Towards this purpose, we first rescaled the signals from different sensors, pixel by pixel, using a new signal rescaling method that is robust to limited overlapping observations among sensors. We then corrected the monthly signal differences between the C-band and the scaled Ku-band signals, by modelling the signal differences from climatic variables (i.e., monthly precipitation, skin temperature, and snow depth) using decision tree regression. The quality of the merged radar signal was assessed by computing the Pearson r, Root Mean Square Error (RMSE), and relative RMSE (rRMSE) between the C-band and the corrected Ku-band signals in the overlapping years (1999–2001 and 2007–2009). We obtained high Pearson r values and low RMSE values at both the regional (r ≥ 0.93, RMSE ≤ 0.16, rRMSE ≤0.37) and pixel levels (median r across pixels ≥ 0.80, median RMSE ≤ 0.38, median rRMSE ≤ 0.64), suggesting high accuracy for the data merging procedure. The merged radar signal was then validated with a continuous ERS-2 data set available between 1995 and 2011. ERS-2 stopped working in full mode after 2001 but observations are occasionally available for a subset of the pixels until 2011. Because the period of 1995–2011 fully overlaps with the working period of QSCAT (1999–2009), comparing the merged radar signal against the ERS-2 data in 1995–2011 is the most direct validation available. We found concordant monthly dynamics between the merged radar signals and the ERS-2 signals during 1995–2011, with Pearson r value ranging from 0.79 to 0.98 across regions. These results evidenced that our merged radar data have a consistent C-band signal dynamic. The CScat data set (https://doi.org/10.6084/m9.figshare.20407857, Tao et al. 2022a) is expected to advance our understanding of the long-term changes in, e.g., global vegetation and soil moisture. The data set will be updated on a regular basis
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