A Delicate Balance Between Spin-Wave Mediated Weak Localization and Electron-Phonon Scattering in the Design of Zero Temperature Coefficient of Resistivity.

Zero thermal coefficients of resistivity (ZTCR) materials exhibit minimal changes in resistance with temperature variations, making them essential in modern advanced technologies. The current ZTCR materials, which are based on the resistivity saturation effect of heavy metals, tend to function at elevated temperatures because the mean free path approaches the lower limit of the semiclassical Boltzmann theory when the temperature is sufficiently high. ZTCR materials working at low-temperatures are difficult to achieve due to electron-phonon scattering, which results in increased resistivity according to Bloch's theory. In this work, the ZTCR behavior at low-temperatures is realized in pre-microstrained Mn3NiN. The delicate balance between the resistivity contribution from electron-phonon scattering and spin-wave mediated weak localization is well revealed. A remarkable temperature coefficient of resistivity (TCR) value as low as 1.9 ppm K-1 (50 K ≤ T ≤ 200 K) is obtained, which is significantly superior to the threshold value of ZTCR behavior and the application standard of commercial ZTCR materials. The demonstration provides a unique paradigm in the design of ZTCR materials through the contraction effects of two opposite conductance mechanisms with positive and negative thermal coefficients of resistivity.

An optimal ensemble of the CoLM for simulating the carbon and water fluxes over typical forests in China.

Stomatal conductance (gs) and compensatory water uptake (CWU) are crucial processes in land surface models, as they directly influence the exchange of carbon and water fluxes between terrestrial ecosystems and the atmosphere. In this study, we integrated a new stomatal scheme derived from optimal stomatal theory (Medlyn's gs model), and an empirical CWU scheme into the Common Land Model (CoLM). Assessing the impacts on modeling gross primary productivity (GPP) and latent flux (LE) through observations obtained from eddy covariance (EC) measurements at three forest sites in China. Our results show that replacing the Ball-Berry's gs model (termed BB) with Medlyn's gs model (termed MED) did not bring about significant changes (had neutral impacts) in the performance of CoLM simulations at three forest sites. Considering the climate factors of annual mean precipitation to optimize key fitting parameters in gs exhibited improvement in model simulations. The average coefficient of determination (R2) achieved to 0.65 for GPP and LE at three sites, and the normalized root mean squared error (NRMSE) decreased from 0.83 to 0.77 at those sites. Besides, incorporating CWU into the model improved its performance. The R2 increased to 0.84 and RMSE decreased to 4.84 µmol m-2 s-1 for GPP, and the R2 increased to 0.62 and RMSE decreased to 55.64 W m-2 for LE. Therefore, modifying the model process of both contributed more to enhancing the model simulations than relying solely on one of these functions. Our study highlights that the response of plant functional types (PFTs) to water stress can be effectively represented in gs models when coupled with biochemical capacity to quantify carbon and water fluxes in forest ecosystems or other ecosystems.

The increasing rate of net carbon uptake in Eurasia has been declining since the early 2000s.

The analysis of terrestrial ecosystem carbon dynamics, based on scarce carbon flux observations or carbon flux products simulated by reanalysis meteorological data, has great uncertainties. A more accurate understanding of carbon dynamics in Eurasia was achieved by using a carbon flux dataset (CFD) from meteorological stations with quasi-observational characteristics. The growth of net carbon uptake of ecosystems over Eurasia has been decreasing since the early 2000s. The net ecosystem productivity (NEP) increased significantly with the growth rate of 8.7 × 10-3 g C m-2d-1 yr-1 in spring, summer, and autumn (SSA) during 2003-2011 (p < 0.05), which was correlated with the enhanced vegetation index (EVI) and land surface water index (LSWI). This growth was mostly in dry subhumid and humid regions. However, the change in Eurasian NEP was not significant after 2011. Additionally, about 79 % of the stations in Eurasia were in net carbon uptake in SSA, and net carbon emission stations were mainly located in southwestern Eurasia. The intensity of net carbon uptake was highest in the forest, with a mean carbon uptake of 1.73 ± 0.76 g C m-2d-1 in SSA during 2003-2018, and almost all stations demonstrated carbon uptake. During 2011-2018, the number of stations experiencing reduced NEP exceeded those with increased NEP, and this ratio was higher compared to 2003-2011, mainly due to the decrease in EVI and LSWI. The rate of NEP decline at stations with reduced NEP was 5.2 × 10-3 g C m-2d-1 yr-1 faster during 2011-2018 than in the previous period (p < 0.01). Most of the decreases in NEP during 2011-2018 occurred in cropland, grassland and urban land. The spatio-temporal dynamic analysis of Eurasian NEP could provide references for effective carbon management.

Trade-offs and synergistic relationships of ecosystem services under land use change in Xinjiang from 1990 to 2020: A Bayesian network analysis.

Ecosystem service value (ESV) refers to the value of benefits provided by the ecosystem to people, and can reflect the quality of regional ecological environment. There have been few studies on ESV in arid regions experiencing dramatic land use changes. Also, many past ESV studies have obtained distorted results by using a simple linear function to examine the trade-offs between driving factors. This study quantified ESV in Xinjiang from 1990 to 2020 based on value equivalent method. Differences in ESV among ecosystem services in Xinjiang under different scenarios were simulated using a Bayesian network model. The results demonstrated land use changes in Xinjiang from 1990 to 2020, with construction land expanding the most significantly (dynamic index: 224.63 %), whereas grassland area decreased (dynamic index: -1.31 %) due to transformation to unused and cultivated land. ESV in Xinjiang presented an N-shaped variation trend from 1990 to 2020 and decreased by 309.6 × 108 CNY, with a variation rate of -20.35 %. The rank of the four categories of ecological services from 1990 to 2020 in terms of ESV was: regulating services > support services > cultural services > supply services. There was a gradual reduction in ESV in Xinjiang from 1990 to 2020. The rank of the different regions in terms of the reduction in ESV was: Northern Xinjiang (295.24 × 108 CNY) > Southern Xinjiang (280.94 × 108 CNY) > Eastern Xinjiang (109.76 × 108 CNY). Land use change was a direct driver of changes in ESV, whereas natural and social factors, such as precipitation, temperature, population, and policy factors, were indirect drivers. This study can act as a reference for sustainable management of ecosystem services in arid regions.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Quantifying the response of surface urban heat island to urban greening in global north megacities.

Urban heat island, a phenomenon that urban temperature is higher than the rural area nearby, affects directly citizens' human health and well-being. However, the cooling effect from urban green space (UGS) and the attribution of the different land processes to surface urban heat island intensity (SUHI) under different background climates remains unclear. The coarse-grained model was used to estimate summer SUHI in three different background climatic zones and for seven agglomerations (BTH, JP, LD, NAAC, NAGL, YZ, UQ). Results indicate that (1) the temperate zone had the highest daytime SUHI (0-10 °C), while the arid zone has the lowest daytime SUHI (-1-2 °C). In both temperate and cold zone, the daytime SUHI was higher than the nighttime SUHI. The SUHI in downtown was higher (more than 2 °C) than in the suburbs. (2) The increasing precipitation can enhance daytime SUHI while can weaken nighttime SUHI in all three climatic zones. The increasing temperature tends to enhance SUHI in both daytime and nighttime (exclude UQ). (3) The cooling effects of UGS in daytime SUHI were highly dependent on the background climate (cold > temperate > arid). (4) The nighttime SUHI could be effectively offset when UGSFs were greater than 0.48, 0.82, 0.97, 0.95 in NAAC, NAGL, YZ, and UQ. This article highlights the different feedback of urban green space to UHII and supports green infrastructure intervention as an effective means of reducing urban heat stress at urban agglomeration scales.

Negative Thermal Expansion over a Wide Temperature Range in Fe-Doped MnNiGe Composites.

Fe-doped MnNiGe alloys were successfully synthesized by solid-state reaction. Giant negative thermal expansion (NTE) behaviors with the coefficients of thermal expansion (CTE) of -285.23 × 10-6 K-1 (192-305 K) and -1167.09 × 10-6 K-1 (246-305 K) have been obtained in Mn0.90Fe0.10NiGe and MnNi0.90Fe0.10Ge, respectively. Furthermore, these materials were combined with Cu in order to control the NTE properties. The results indicate that the absolute value of CTE gradually decreases with increasing Cu contents. In Mn0.92Fe0.08NiGe/x%Cu, the CTE gradually changes from -64.92 × 10-6 K-1 (125-274 K) to -4.73 × 10-6 K-1 (173-229 K) with increasing value of x from 15 to 70. The magnetic measurements reveal that the NTE behaviors in this work are strongly correlated with the process of the magnetic phase transition and the introduction of Fe atoms could also change the spiral anti-ferromagnetic (s-AFM) state into ferromagnetic (FM) state at low temperature. Our study launches a new candidate for controlling thermal expansion properties of metal matrix materials which could have potential application in variable temperature environment.

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012.

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

Vegetation changes and land surface feedbacks drive shifts in local temperatures over Central Asia.

Vegetation changes play a vital role in modifying local temperatures although, until now, the climate feedback effects of vegetation changes are still poorly known and large uncertainties exist, especially over Central Asia. In this study, using remote sensing and re-analysis of existing data, we evaluated the impact of vegetation changes on local temperatures. Our results indicate that vegetation changes have a significant unidirectional causality relationship with regard to local temperature changes. We found that vegetation greening over Central Asia as a whole induced a cooling effect on the local temperatures. We also found that evapotranspiration (ET) exhibits greater sensitivity to the increases of the Normalized Difference Vegetation Index (NDVI) as compared to albedo in arid/semi-arid/semi-humid regions, potentially leading to a cooling effect. However, in humid regions, albedo warming completely surpasses ET cooling, causing a pronounced warming. Our findings suggest that using appropriate strategies to protect vulnerable dryland ecosystems from degradation, should lead to future benefits related to greening ecosystems and mitigation for rising temperatures.