2022
DOI: 10.1016/j.jclepro.2022.134734
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Effects of projected climate change on winter wheat yield in Henan, China

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Cited by 19 publications
(8 citation statements)
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“…As two major wheat production provinces in China, in 2021 Henan's wheat fields accounted for more than 20% of the total cultivated area of China and 25% of the country's wheat production while Shandong was the second largest wheat‐producing province accounting for about 17% of the total cultivated area of China (Table 6). 54 In line with this, wheat‐sourced food contributed most to Zn intake for the populations in Henan and Shandong (Table 4). On the contrary, the populations in Guangxi, Guizhou, Hubei, Jiangsu, Hunan and Liaoning mainly consumed rice‐sourced food where areas corresponded to larger areas under rice than wheat (Table 6).…”
Section: Discussionsupporting
confidence: 54%
“…As two major wheat production provinces in China, in 2021 Henan's wheat fields accounted for more than 20% of the total cultivated area of China and 25% of the country's wheat production while Shandong was the second largest wheat‐producing province accounting for about 17% of the total cultivated area of China (Table 6). 54 In line with this, wheat‐sourced food contributed most to Zn intake for the populations in Henan and Shandong (Table 4). On the contrary, the populations in Guangxi, Guizhou, Hubei, Jiangsu, Hunan and Liaoning mainly consumed rice‐sourced food where areas corresponded to larger areas under rice than wheat (Table 6).…”
Section: Discussionsupporting
confidence: 54%
“…The growing period decreased by 3.6 days, 4.7 days, and 5.0 days per decade in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, which were compared to others. Zhang et al, found that the growing period of winter wheat would be shortened by 0.84 days per decade in the combination model of BCCT63 and WOFOST [63]. Li et al, found that the growing period from sowing to ripening in the RCP8.5 climate scenario would be shortened by 4 days and 15 days in the periods 2010-2039 and 2040-2069, respectively [64].…”
Section: Discussionmentioning
confidence: 99%
“…Due to the limited availability of observational data on surface dust emissions and the high concentration of coarse particulate pollutants during dust weather events, we compared the measurements of coarse PM concentration (PM 10‐2.5 ) with the simulated values to assess the performance of the WRF‐Chem model. To evaluate the meteorological and pollutant simulation results, we employed five statistical metrics: mean bias (MB), normalized mean bias (NMB), normalized mean error (NME), root mean square error (RMSE), and correlation coefficient (R) (Ru et al, 2022; Song et al, 2017; Zhang, Wang, et al, 2022). The calculation method for these statistical metrics can be found in Table 2.…”
Section: Methodsmentioning
confidence: 99%