• Energy Research

The soil moisture daily diagnostic equation (SMDE) evaluates the relationship between the loss function coefficient and the summation of the weighted average of precipitation. The loss function coefficient uses the day of the year (DOY) to approximate the seasonal changes in soil moisture loss for a given location. Solar radiation is the source of the energy that drives the complex and intricates of the earth-atmospheric processes and biogeochemical cycles in the environment. Previous research assumed DOY is the approximation of other environmental factors (e.g., temperature, wind speed, solar radiation). In this article, two solar radiation parameters were introduced,i.e., the actual solar radiation and the clear sky solar radiation and were incorporated into the loss function coefficient to improve its estimation. This was applied to 2 years of continuous rainfall, soil moisture data from USDA soil climate network (SCAN) sites AL2053, GA2027 MS2025, and TN2076. It was observed that the correlation coefficient between the observed soil moisture and B values (which is the cumulated average of rainfall to soil moisture loss) increased on average by 2.3% and the root mean square errors (RMSEs) for estimating volumetric soil moisture at columns 0–5, 0–10, 0–20, 0–50, 0–100 cm reduced on average by 8.6% for all the study sites. The study has confirmed that using actual solar radiation data in the soil moisture daily diagnostic equation can improve its accuracy.

Quantification of the trade-offs among greenhouse gas (GHG) emissions, yield, and farmers’ incomes is essential for proposing economic and environmental nitrogen (N) management strategies for optimizing agricultural production. A four-year (2017–2020) field experiment (including four treatments: basic N fertilizer treatment (BF), suitable utilization of fertilization (SU), emission reduction treatment (ER), and high fertilization (HF)) was conducted on maize (Zea mays L.) in the North China Plain. The Life Cycle Assessment (LCA) method was used in this study to quantify the GHG emissions and farmers’ incomes during the whole maize production process. The total GHG emissions of BF, SU, ER, and HF treatments in the process of maize production are 10,755.2, 12,908.7, 11,950.1, and 14,274.5 kg CO2-eq ha−1, respectively, of which the direct emissions account for 84.8%, 76.8%, 74.9%, and 71.0%, respectively. Adding inhibitors significantly reduced direct GHG emissions, and the N2O and CO2 emissions from the maize fields in the ER treatment decreased by 30.0% and 7.9% compared to those in the SU treatment. Insignificant differences in yield were found between the SU and ER treatments, indicating that adding fertilizer inhibitors did not affect farmers’ incomes while reducing GHG emissions. The yield for SU, ER, and HF treatments all significantly increased by 12.9–24.0%, 10.0–20.7%, and 2.1–17.4% compared to BF, respectively. In comparison with BF, both SU and ER significantly promoted agricultural net profit (ANP) by 16.6% and 12.2%, with mean ANP values of 3101.0 USD ha−1 and 2980.0 USD ha−1, respectively. Due to the high agricultural inputs, the ANP values in the HF treatment were 11.2%, 16.6%, and 12.4% lower than those in the SU treatment in 2018–2020. In conclusion, the combination of N fertilizer and inhibitors proved to be an environmentally friendly, high-profit, and low-emissions production technology while sustaining or even increasing maize yields in the North China Plain, which was conducive to achieving agricultural sustainability.

The water and energy in the land surface and lower atmosphere have a strong coupling relationship. Apart from the land surface temperature (Ts) and air temperature (Ta), the land surface-air temperature difference (Ts-Ta) is also an essential parameter reflecting the coupling process. However, the global spatiotemporal variations and influencing factors of Ts-Ta remain not well explored. Here, ERA5-land reanalysis data, GIMMS NDVI data, and elevation data were used to analyze the global spatiotemporal heterogeneity and influencing factors of Ts-Ta. It was found that annual mean Ts-Ta exhibited a decreasing trend from the equator to polar areas. And the annual Ts-Ta increased at 0.009 °C/10a from 1981 to 2020. The variations of global net radiation mainly determined the spatiotemporal heterogeneity of global Ts-Ta. The different properties of the land surface and near-surface atmosphere were the main factors affecting the Ts-Ta, including soil moisture, vegetation, snow cover, and the water vapor content in the atmosphere. In addition, Ts and Ta also affected each other. These findings are conducive to a better understanding of the land-atmosphere coupling, and it is of great significance to take better measures to adapt the global climate change.

Climate change has caused uneven changes in hydrological processes (precipitation and evapotranspiration) on a space-temporal scale, which would influence climate types, eventually impact agricultural production. Based on data from 61 meteorological stations from 1961 to 2014 in the North China Plain (NCP), the spatiotemporal characteristics of climate variables, such as humidity index, precipitation, and potential evapotranspiration (ET0), were analyzed. The sensitivity coefficients and contribution rates were applied to ET0. The NCP has experienced a semiarid to humid climate from north to south due to the significant decline of ET0 (−13.8 mm decade−1). In the study region, 71.0% of the sites showed a “pan evaporation paradox” phenomenon. Relative humidity had the most negative influence on ET0, while wind speed, sunshine hours, and air temperature had a positive effect on ET0. Wind speed and sunshine hours contributed the most to the spatiotemporal variation of ET0, followed by relative humidity and air temperature. Overall, the key climate factor impacting ET0 was wind speed decline in the NCP, particularly in Beijing and Tianjin. The crop yield in Shandong and Henan provinces was higher than that in the other regions with a higher humidity index. The lower the humidity index in Hebei province, the lower the crop yield. Therefore, potential water shortages and water conflict should be considered in the future because of spatiotemporal humidity variations in the NCP.

Global warming and dimming/brightening have significant implications for crop systems and exhibit regional variations. It is important to clarify the changes in regional thermal and solar radiation resources and estimate the impacts on potential crop production spatially and temporally. Based on daily observation data during 1961–2015 in the North China Plain (NCP), the impacts of climate change associated with climate warming and global dimming/brightening on potential light–temperature productivity (PTP) of summer maize were assessed in this study. Results show that the NCP experienced a continuous warming and dimming trend in maize growing season during the past 55 years, and both ATT10 and solar radiation had an abrupt change in the mid-1990s. The period of 2000–2015 was warmer and dimmer than any other previous decade. Assuming the maize growing season remains unchanged, climate warming would increase PTP of summer maize by 4.6% over the period of 1961–2015, which mainly occurred in the start grain filling–maturity stage. On the other hand, as negative contribution value of solar radiation to the PTP was found in each stage, dimming would offset the increase of PTP due to warming climate, and lead to a 15.6% reduction in PTP in the past 55 years. This study reveals that the changes in thermal and solar radiation have reduced the PTP of summer maize in the NCP. However, the actual maize yield could benefit more from climate warming because solar radiation is not a limiting factor for the current low production level.