Synergies between Urban Heat Island and Urban Heat Wave Effects in 9 Global Mega–Regions from 2003 to 2020

Global urbanization significantly impacts the thermal environment in urban areas, yet urban heat island (UHI) and urban heat wave (UHW) studies at the mega–region scale have been rare, and the impact study of urbanization is still lacking. In this study, the MODIS land surface temperature (LST) product was used to depict the UHI and UHW in nine mega–regions globally between 2003 and 2020. The absolute and percentile–based UHW thresholds were adopted for both daily and three–day windows to analyze heat wave frequency, and UHW magnitude as well as frequency were compared with UHI variability. Results showed that a 10% increase in urban built-up density led to a 0.20 °C to 0.95 °C increase in LST, a 0.59% to 7.17% increase in hot day frequency, as well as a 0.08% to 0.95% increase in heat wave number. Meanwhile, a 1 °C increase in UHI intensity (the LST differences between the built-up and Non-built-up areas) led to a 2.04% to 92.15% increase in hot day frequency, where daytime LST exceeds 35 °C and nighttime LST exceeds 25 °C, as well as a 3.30% to 33.67% increase in heat wave number, which is defined as at least three consecutive days when daily maximum temperature exceeds the climatological threshold. In addition, the increasing rates of UHW magnitudes were much faster than the expansion rates of built-up areas. In the mega–regions of Boston, Tokyo, São Paulo, and Mexico City in particular, the increasing rates of UHW hotspot magnitudes were over 2 times larger than those of built-up areas. This indicated that the high temperature extremes, represented by the increase in UHW frequency and magnitudes, were concurrent with an increase in UHI under the context of climate change. This study may be beneficial for future research of the underlying physical mechanisms on urban heat environment at the mega–region scale.

Quantifying how urban landscape heterogeneity affects land surface temperature at multiple scales

Background Landscape metrics have been widely applied to quantifying the relationship between land surface temperature and urban spatial patterns and have received acceptable verification from landscape ecologists but some studies have shown their inaccurate results. The objective of the study is to compare landscape metrics and texture-based measures as alternative indices in measuring urban heterogeneity effects on LST at multiple scales. Results The statistical results showed that the correlation between urban landscape heterogeneity and LST increased as the spatial extent (scale) of under-study landscapes increased. Overall, landscape metrics showed that the less fragmented, the more complex, larger, and the higher number of patches, the lower LST. The most significant relationship was seen between edge density (ED) and LST (r = − 0.47) at the sub-region scale. Texture measures showed a stronger relationship (R2 = 34.84% on average) with LST than landscape metrics (R2 = 15.33% on average) at all spatial scales, meaning that these measures had a greater ability to describe landscape heterogeneity than the landscape metrics. Conclusion This study suggests alternative measures for overcoming landscape metrics shortcomings in estimating the effects of landscape heterogeneity on LST variations and gives land managers and urban planners new insights into urban design.

Determinizing the contributions of human activities and climate change on greening in the Beijing–Tianjin–Hebei Region, China

China accounts for 25% of the global greening. There are temporal and spatial differences of China’s greening and intrinsic driving forces. Thus, it is crucial to determinize the contributions of human activities and climate change on greening at region scale. The Beijing–Tianjin–Hebei Region (BTHR) is one of the most active areas with human activities in China. It is necessary to explore negative or positive impacts of human activities on the regional greening or browning under climate change. A time series of annual vegetation coverage from satellite data was selected to quantify regional greening in the BTHR from 2000 to 2019 and their responses to climate change and human activities. Results showed generally widespread greening over the last 20 years at an average increased rate of 0.036 decade−1 in vegetation coverage (P < 0.01). Overall warmer and wetter climate across the BTHR were positively correlated with regional greening. The positive effects of human activities on greening accounted for 48.4% of the BTHR, especially the benefits of ecological restoration projects and the agricultural activities. Increases in vegetation coverage had resulted from the combined effects of climate change and human activities. Climate change had a stronger influence on vegetation coverage than human activities. Contributions of climate change to greening and browning was about 74.1% and < 20%, respectively. The decrease in vegetation coverage was mainly the results of the inhibition of human activities. More detailed socioeconomic and anthropogenic datasets are required for further analysis. Further research consideration would focus on the nonlinear responses of vegetation to climate change.

Aquifer Depletion in the Arlit Mining Area (Tim Mersoï Basin, North Niger)

Located in northwestern Niger, the Tim Mersoï Basin (TMB) is an important mining region in the scale of West Africa. Groundwater is considered the main source of fresh water in the basin, especially for mining activities. It, therefore, appears essential to monitor their responses to these activities. However, no study has been carried out in the Tim Mersoï Basin. This study aims to evaluate the groundwater storage changes (GWSC) of the TMB and to analyze the spatio-temporal evolution of the Tarat aquifer under the effect of mining activities in the Arlit region. For this purpose, Gravity Recovery And Climate Experiment (GRACE), Global Land Data Assimilation System (GLDAS), and in-situ data were used. The results show a variation of the GWS from 2002 to 2019 of about −0.1310 cm/year on the scale of the basin and −0.0109 cm/year in the Arlit mining area. The GWSC at the basin scale and the one at the Arlit region scale were shown to be linked with an RMSE between the two datasets of 0.79. This shows the potential of GRACE for contextualizing studies in small areas. The study also highlighted that the groundwater flow direction was highly modified; the drawdown of the Tarat water table was more than 50 m in the areas heavily impacted by mining activities, with an increasing intensity from the northwest to the southeast of Arlit.

Evaluation of Microbe-Driven Soil Organic Matter Quantity and Quality by Thermodynamic Theory

ABSTRACT Microbial communities, coupled with substrate quality and availability, regulate the stock (formation versus mineralization) of soil organic matter (SOM) in terrestrial ecosystems. However, our understanding of how soil microbes interact with contrasting substrates influencing SOM quantity and quality is still very superficial. Here, we used thermodynamic theory principles and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) to evaluate the linkages between dissolved organic matter (DOM [organic substrates in soil that are readily available]), thermodynamic quality, and microbial communities. We investigated soils from subtropical paddy ecosystems across a 1,000-km gradient and comprising contrasting levels of SOM content and nutrient availability. Our region-scale study suggested that soils with a larger abundance of readily accessible resources (i.e., lower Gibbs free energy) supported higher levels of microbial diversity and higher SOM content. We further advocated a novel phylotype-level microbial classification based on their associations with OM quantities and qualities and identified two contrasting clusters of bacterial taxa: phylotypes that are highly positively correlated with thermodynamically favorable DOM and larger SOM content versus those which are associated with less-favorable DOM and lower SOM content. Both groups are expected to play critical roles in regulating SOM contents in the soil. By identifying the associations between microbial phylotypes of different life strategies and OM qualities and quantities, our study indicates that thermodynamic theory can act as a proxy for the relationship between OM and soil microbial communities and should be considered in models of soil organic matter preservation. IMPORTANCE Microbial communities are known to be important drivers of organic matter (OM) accumulation in terrestrial ecosystems. However, despite the importance of these soil microbes and processes, the mechanisms behind these microbial-SOM associations remain poorly understood. Here, we used the principles of thermodynamic theory and novel Fourier transform ion cyclotron resonance mass spectrometry techniques to investigate the links between microbial communities and dissolved OM (DOM) thermodynamic quality in soils across a 1,000-km gradient and comprising contrasting nutrient and C contents. Our region-scale study provided evidence that soils with a larger amount of readily accessible resources (i.e., lower Gibbs free energy) supported higher levels of microbial diversity and larger SOM content. Moreover, we created a novel phylotype-level microbial classification based on the associations between microbial taxa and DOM quantities and qualities. We found two contrasting clusters of bacterial taxa based on their level of association with thermodynamically favorable DOM and SOM content. Our study advances our knowledge on the important links between microbial communities and SOM. Moreover, by identifying the associations between microbial phylotypes of different life strategies and OM qualities and quantities, our study indicates that thermodynamic theory can act as a proxy for the relationship between OM and soil microbial communities. Together, our findings support that the association between microbial species taxa and substrate thermodynamic quality constituted an important complement explanation for soil organic matter preservation.

The potential land requirements and related land use change emissions of solar energy

Although the transition to renewable energies will intensify the global competition for land, the potential impacts driven by solar energy remain unexplored. In this work, the potential solar land requirements and related land use change emissions are computed for the EU, India, Japan and South Korea. A novel method is developed within an integrated assessment model which links socioeconomic, energy, land and climate systems. At 25–80% penetration in the electricity mix of those regions by 2050, we find that solar energy may occupy 0.5–5% of total land. The resulting land cover changes, including indirect effects, will likely cause a net release of carbon ranging from 0 to 50 gCO2/kWh, depending on the region, scale of expansion, solar technology efficiency and land management practices in solar parks. Hence, a coordinated planning and regulation of new solar energy infrastructures should be enforced to avoid a significant increase in their life cycle emissions through terrestrial carbon losses.

Processing of Different Temporal Scales in the Human Brain

While recalling life events, we reexperience events of different durations, ranging across varying temporal scales, from several minutes to years. However, the brain mechanisms underlying temporal cognition are usually investigated only in small-scale periods—milliseconds to minutes. Are the same neurocognitive systems used to organize memory at different temporal scales? Here, we asked participants to compare temporal distances (time elapsed) to personal events at four different temporal scales (hour, day, week, and month) under fMRI. Cortical activity showed temporal scale sensitivity at the medial and lateral parts of the parietal lobe, bilaterally. Activity at the medial parietal cortex also showed a gradual progression from large- to small-scale processing, along a posterior–anterior axis. Interestingly, no sensitivity was found along the hippocampal long axis. In the medial scale-sensitive region, most of the voxels were preferentially active for the larger scale (month), and in the lateral region, scale selectivity was higher for the smallest scale (hour). These results demonstrate how scale-selective activity characterizes autobiographical memory processing and may provide a basis for understanding how the human brain processes and integrates experiences across timescales in a hierarchical manner.

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

The 2012–2018 drought was such an extreme event in the drought-prone area of Northeast Brazil that it triggered a discussion about proactive drought management. This paper aims at understanding the causes and consequences of this event and analyzes its frequency. A consecutive sequence of sea surface temperature anomalies in the Pacific and Atlantic Oceans, at both the decadal and interannual scales, led to this severe and persistent drought. Drought duration and severity were analyzed using run theory at the hydrographic region scale as decision-makers understand impact analysis better at this scale. Copula functions were used to properly model drought joint characteristics as they presented different marginal distributions and an asymmetric behavior. The 2012–2018 drought in Ceará State had the highest mean bivariate return period ever recorded, estimated at 240 years. Considering drought duration and severity simultaneously at the level of the hydrographic regions improves risk assessment. This result advances our understanding of exceptional events. In this sense, the present work proposes the use of this analysis as a tool for proactive drought planning.

Unlocking Galactic Wolf–Rayet stars with Gaia DR2 – I. Distances and absolute magnitudes

ABSTRACT We obtain distances to 383 Galactic Wolf–Rayet (WR) stars from Gaia DR2 parallaxes and Bayesian methods, with a prior based on H ii regions and dust extinction. Distances agree with those from Bailer-Jones et al. for stars up to 2 kpc from the Sun, though deviate thereafter due to differing priors, leading to modest reductions in luminosities for recent WR spectroscopic results. We calculate visual and K-band absolute magnitudes, accounting for dust extinction contributions and binarity, and identify 187 stars with reliable absolute magnitudes. For WR and O stars within 2 kpc, we find a WR/O ratio of 0.09. The distances are used to generate absolute magnitude calibrations and obtain the Gaia colour–magnitude diagram for WR stars. Average vWR-band absolute magnitudes for WN stars range from –3.6 mag (WN3–4) to –7.0 mag (WN8–9ha), and –3.1 (WO2–4) to –4.6 mag (WC9), with standard deviations of ∼0.6 mag. Using H ii region scale heights, we identify 31 WR stars at large (3σ, |z| ≥ 156 pc) distances from the mid-plane as potential runaways accounting for the Galactic warp, of which only four involve WN8–9 stars, contrary to previous claims.