The Synergistic Production Effect of Water and Nitrogen on Winter Wheat in Southern Xinjiang.

Water and nitrogen management are crucial for food security and the efficient use of water and fertilizer, especially in arid regions. Three irrigation levels, namely, 80% crop water requirement (ETC) (W1), 100% ETC (W2), and 120% ETC (W3), and three nitrogen application levels, namely, 0 kg/ha (N1), 207 kg/ha (N2), and 276 kg/ha (N3), were used as the experimental treatments, and a control group, denoted as CK, was created. The results show that the maximum height achieved was 82.16 cm under W3N3. There was a single-peak variation trend throughout the growth stages of SPAD. It peaked at 58.44 under W3N3 and then at 27.9 under W2N2. The net photosynthetic and transpiration rates displayed bimodal peaks and the phenomenon of a "photosynthetic midday depression". And the prominent peaks in leaf water use efficiency occurred at 14:00 and 18:00, alongside noteworthy enhancements observed under the W3 treatment. Water and nitrogen and their interactions significantly affected the dry matter (DM) of winter wheat, with the spike accounting for the highest percentage. The W2N2 treatment demonstrated superior effectiveness in enhancing winter wheat water use efficiency, offering the potential to decrease irrigation requirements by 20% and nitrogen application by 25%. Moreover, the maximum PFPN attained under W2N2 reached 60.13, representing a noteworthy 35.25% increase compared to the control group (CK), but the HI of the W2N2 treatment only reached 0.56. The highest HI was achieved with W3N2 (0.73), and the nitrogen application of 207 kg/ha was more conducive to obtaining a higher HI. The highest yield was achieved under W3N3 (13.599 t/ha), followed by W2N2 (12.447 t/ha), and the spike proportion exceeded 60% with W2N2, and its production cost and economic benefit ratio of under 0.31 were superior to those for other treatments. Multiple regression analysis revealed that the maximum yield reached 12.944 t/ha with an irrigation amount of 3420.1 m3/ha and a nitrogen application of 251.92 kg/ha. Overall, our study suggests using an optimal water-nitrogen combination, specifically an irrigation level of 2829 m3/ha and a nitrogen application rate of 207 kg/ha, leading to increased winter wheat yields and economic benefits. These research results provide a pragmatic technique for improving winter wheat production in southern Xinjiang.

Clean and efficient synthesis of LiFePO4 cathode material using titanium white waste and calcium dihydrogen phosphate.

Large amounts of titanium white waste are generated in the production of titanium dioxide using sulphate method, which in turn can be used to prepare LiFePO4 cathode material, thereby reducing environmental risks and achieving resource recovery. However, a key challenge lies in the elimination of impurities. In this work, a cost-efficient and straightforward approach based on phase transformation during hydrothermal treatment was proposed to utilize titanium white waste with calcium dihydrogen phosphate for the preparation of LiFePO4 cathode material. The content of Fe in the leachate was enriched to 81.5 g/L after purification, while 99.9 % of Ti and 98.36 % of Al and were successfully removed. In the subsequent process for Fe/P mother liquor preparation, the losses of Fe and P were only 5.82 % and 2.81 %, respectively. The Fe and P contents of the synthesized FePO4 product were 29.47 % and 17.08 %, respectively, and the Fe/P molar ratio was 0.986. Crystal phase of the product matched well with standard iron phosphate, and the lamellar microstructure of FePO4 was uniform with the particle size ranging from 3 to 5 µm. Moreover, the contents of impurities in the product were far below the standard. The initial discharge of LiFePO4 synthesized by the iron phosphate was 160.6 mAh.g-1 at 0.1C and maintained good reversible capacity after 100 cycles. This work may provide new strategy for preparing LiFePO4 cathode material from industrial solid waste.

Identification and prediction of climate factors based on factor analysis and a grey prediction model in China.

Identifying and predicting the impacts of climate change are crucial for various purposes, such as maintaining biodiversity, agricultural production, ecological security, and environmental conservation in different regions. In this paper, we used the surface pressure (SP), surface temperature (ST), 2-m air temperature (AT), 2-m dewpoint temperature (DT), 10-m wind speed (WS), precipitation (PRE), relative humidity (RH), actual evapotranspiration (ETa), potential evapotranspiration (ETP), total solar radiation (TRs), net solar radiation (NRs), UV intensity (UVI), sunshine duration (SD), convective available potential energy (CAPE) as factors in our climate modeling. The spatiotemporal distribution characteristics of the climate factors were analyzed and identified based on historical data for China from 1950 to 2020 using factor analysis and a grey model (GM (1,1)), and their future change characteristics were predicted. The results show that there is a strong correlation between climate factors. ST, AT, DT, PRE, RH, and ETa are the main factors that have the potential to cause heavy rain, thunderstorms, and other severe weather. Meanwhile, PRE, RH, TRs, NRs, UVI, and SD are among the major factors linked to climate change. Specifically, SP, ST, AT, and WS are among the minor factors in most areas. The top ten provinces in terms of combined factor scores are Heilongjiang, Neimenggu, Qinghai, Beijing, Shandong, Xizang, Shanxi, Tianjin, Guangdong, and Henan. The trend of climate factors in China is expected to remain relatively stable over the next 30 years, with a noteworthy decrease observed in CAPE compared to the past 71 years. Our findings can help to better mitigate the risks associated with climate change and enhance resilience; they also provide a scientific basis for environmental, ecological, and agricultural systems to cope with climate change.