Biochar application is an important measure to regulate SOC. However, the effects of biochar application on soil respiration and SOC fraction of the saline soil have been scarcely investigated. Therefore, in this study, we monitored the annual SOC, nutrients, temperature, water content, and respiration rate under three maize-straw-derived biochar application doses (0, 15, and 30 t∙hm⁻²). Biochar enriched the soil in terms of fast-acting potassium and phosphorus, alkali-hydrolyzable N, ${\mathrm{NO}}_3^{-}$-N, and ${\mathrm{NH}}_4^{+}$-N to varying degrees. One-time biochar application in the trial year continued to fertilizer retention in the following year. Mineral-associated organic carbon and SOC contents increased with time after biochar application, whereas the changes in particulate organic carbon content were the opposite; soil respiration rate was reduced by 7.7–14.7%, and the reduction increased with the dose as well in successive years. The soil respiration rate and soil temperature showed a significant linear correlation, but the application of a high amount of biochar reduced the correlation between the two. Considering the soil respiration rate and physicochemical properties, the best biochar application rate for saline soil is suggested to be 30 t∙hm⁻². This study is of great significance for soil carbon sequestration, emission reduction in saline areas, and the realization of a “carbon peak” in the sense of farmland.

Soil salinization is a global issue confronting humanity, imposing significant constraints on agricultural production in the irrigated regions along the southern bank of the Yellow River. This, in turn, leads to the degradation of the ecological environment and inadequate grain yields. Hence, it is essential to explore the magnitude and spatial patterns of soil salinization to promote efficient and sustainable agricultural development. This study carried out a two-year surface soil sampling experiment encompassing the periods before spring irrigation and the budding, flowering, and maturity stages of sunflower fields in the irrigated area along the southern bank of the Yellow River. It employed deep learning in conjunction with multispectral remote sensing conducted by UAV to estimate soil salinity levels in the sunflower fields. Following the identification of sensitive spectral variables through correlation analysis, we proceeded to model and compare the accuracy and stability of various models, including the deep learning Transformer model, traditional machine learning BP neural network (BPNN), random forest model (RF), and partial least squares regression model (PLSR). The findings indicate that the precision of soil salinity content (SSC) retrieval in saline–alkali land can be significantly enhanced by incorporating the RE band of UAV data. Four SSC inversion models were developed using the most suitable spectral variables, resulting in precise soil salinity inversion. The model order based on accuracy and stability was Transformer > BPNN > RF > PLSR. Notably, the Transformer model achieved a prediction accuracy exceeding 0.8 for both the training and test datasets, as indicated by R² values. The precision order of the soil salinity inversion model in each period is as follows: before spring irrigation > budding period > maturity period > flowering stages. Additionally, the accuracy is higher in the bare soil stage compared to the crop cover stage. The Transformer model exhibited RMSE and R² values of 2.41 g kg⁻¹ and 0.84 on the test datasets, with the salt inversion results aligning closely with field-measured data. The results showed that the Transformer deep learning model integrated with RE band data significantly enhances the precision and efficiency of soil salinity inversion within the irrigated regions along the south bank of the Yellow River.

Biochar is a widely recognized soil amendment used to improve soil physicochemical properties and crop productivity. However, its compositive effects on soil water, fertilizer, and carbon in cropping systems are not extensively understood. A two-year field study was conducted to investigate the influence of integrating maize-residue-derived biochar on evapotranspiration, water and fertilizer utilization efficiency, soil organic carbon (SOC) content, and soil carbon emissions in maize farming, employing drip irrigation in conjunction with film mulching. The treatments included the following three biochar amendments: 15 (B15); 30 (B30); and 45 (B45) t ha⁻¹. Biochar was exclusively incorporated prior to sowing during the initial year of the experiment, and no biochar was used as a control (CK). After two years, the biochar amendments, especially B30, improved crop water productivity and the partial factor productivities of nitrogen, phosphorus, and potassium fertilizer. Relative to CK, the biochar amendments significantly reduced soil CO₂ and CH₄ emissions during crop growth by 17.6–40.6% and −1.21–268.4%, respectively, averaged across two years. The best treatment effect was achieved by adding 15 t ha⁻¹ of biochar. The biochar needed replenishing in the third year for B30 and in the fourth year for B45 to increase the SOC content by 20 g kg⁻¹. An application rate of 22 metric tons per hectare of biochar is proposed to optimize water and fertilizer utilization efficiency, alongside augmenting the soil organic matter content, within maize farming under drip irrigation and mulching practices on sandy loam soil. However, the biochar must be added at 20 t ha⁻¹ in the third year to counterbalance soil carbon losses and improve SOC.

“Peak carbon and neutrality”, also known as dual carbon, is the key to solving the problems of energy and industrial low-carbon transformation, and is also fundamental to promoting the development of new industries that protect the environment and conserve resources. Among the cities along the Yellow River Basin, the city of Luoyang in Henan province is strategically vital in the coordinated development of the regional economy. Thus, researching the coupling of urbanisation and ecological protection is an important way to realise the dual carbon goal. To explore the coupling and coordination (CC) between urbanisation and the ecological environment, an index system is built for comprehensively assessing urbanisation and ecological environment (UEE) systems in Luoyang, and a coupling model to measure their coordination degree, quantitatively analyzed the CC process and evolution trend of Luoyang’s UEE, and explored the driving factors causing their changes through regression analysis. The results show that the integrated urbanisation development index of Luoyang ranges from 0.7571–0.9497; however, the contribution of the city’s population to urbanisation is the lowest at only 5.231%. Therefore, it is suggested that the government and other institutions should pay more attention to coordinating the human–land relationship when planning for urban development. The integrated ecological environment development index ranges from 0.7512–0.8266. The contribution ratio of the ecological environment state and pressure on the ecological environment is relatively high, at 27.9% and 48.7%, respectively. Therefore, the city of Luoyang city should reduce the emission of industrial pollutants and improve the environmental level. In addition, the CC degree of UEE of Luoyang ranges from 0.8131–0.9296 during 2016–2021, with an overall trend of steady increase, and the coupling correlation coefficient of R² = 0.9335, with a good overall coupling effect. The results show that Luoyang needs to further accelerate its industrial transformation and upgrading and spatial development strategy, and strive to become an environment-optimised city. This study provides scientific and practical suggestions for the CC development of urbanisation and environment in the city of Luoyang, Henan province, and has reference value for accelerating the realisation of the two-carbon strategy.

Root growth and development of maize (Zea mays L.) is an important process in determining grain yield. The effects of combined fulvic acid (FA, potassium humate as FA source) and super absorbent polymer (SAP) uses on maize root growth and yield were studied. A 2×3 factorial field experiment was applied by combining two SAP doses (0, 45 kg ha^-1) and three FA rates (0, 1, and 2 g L^-1) over 2 yr. Super absorbent polymer was applied to upper 20 cm soil layer at sowing, and FA solutions (1 or 2 g L^-1, corresponding to FA₁ and FA₂) were sprayed onto the canopy three times during growing season. Root parameters, including root biomass, root length density (RLD), root surface-area density (RSD), and root diameter, were determined in the top 40 cm soil layer. Relative to control plants, both chemicals significantly increased root biomass, but these effects were not significantly different from their combined use. Compared to individual FA or SAP treatment, combined applications increased RLD and RSD in 0-20 cm depth. The combined SAP and FA₂ improved RLD at 0-10 cm by 32% compared to FA₂ treatment alone and by 82% compared to non-chemicals control plots over 2 yr. Averaged root diameters also significantly increased in the 40 cm soil layer in FA and SAP treatments alone compared to control, but they were not significantly different with the combined treatment. Similar patterns were found for maize yield each year. The combined application of SAP (45 kg ha^-1) and FA₂ (2 g L^-1) greatly increased root length density and biomass than their individual application, and it could be suitable for high production of maize grown under low rainfall conditions.