ALBERT

Description: The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

Description: The spatial and angular emission patterns of artificial and natural light emitted, scattered, and reflected from the Earth at night are far more complex than those for scattered and reflected solar radiation during daytime. In this commentary, we use examples to show that there is additional information contained in the angular distribution of emitted light. We argue that this information could be used to improve existing remote sensing retrievals based on night lights, and in some cases could make entirely new remote sensing analyses possible. This work will be challenging, so we hope this article will encourage researchers and funding agencies to pursue further study of how multi-angle views can be analyzed or acquired.

Description: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Description: High-elevation, low-relief surfaces are widespread in many mountain belts. However, the origin of these surfaces has long been debated. In particular, the southeast Tibetan Plateau has extensive low-relief surfaces perched above deep valleys and in the headwaters of three of the world’s largest rivers (Salween, Mekong, and Yangtze Rivers). Various geologic data and geodynamic models show that many mountain belts grow first to a certain height and then laterally in an outward propagation sequence. By translating this information into a kinematic propagating uplift function in a landscape evolution model, we propose that the high-elevation, low-relief surfaces in the southeast Tibetan Plateau are simply a consequence of mountain growth and do not require a special process to form. The propagating uplift forms an elongated river network geometry with broad high-elevation, low-relief headwaters and interfluves that persist for tens of millions of years, consistent with the observed geochronology. We suggest that the low-relief interfluves can be long-lived because they lack the drainage networks necessary to keep pace with the rapid incision of the large main-stem rivers. The propagating uplift also produces spatial and temporal exhumation patterns and river profile morphologies that match observations. Our modeling therefore reconciles geomorphic observations with geodynamic models of uplift of the southeast Tibetan Plateau, and it provides a simple mechanism to explain the low-relief surfaces observed in several mountain belts on Earth.

Description: Fracability is a property widely used to evaluate whether reservoirs can effectively fracture to increase production capacity. The brittleness index, which is used to evaluate reservoir fracability, is calculated via various methods, and the evaluation process of the brittleness index is complicated and not sufficiently intuitive. Thus, we used triangle method to evaluate reservoir fracability. The shale composition is classified into strong (quartz + pyrite), moderate (carbonate + plagioclase + siderite), and poor (clay + TOC + porosity) fracability based on the mechanical parameters of each shale component, which were integrated as the endpoints of the triangle method. Meanwhile, the triangle method is divided into four fracability evaluation grades: strong (I), moderate (II), weak (III) and poor (IV) fracability; each major evaluation grade has four sub-categories: best for fracturing (1), better for fracturing (2), poor for fracturing (3) and worst for fracturing (4). The triangle method is simpler and more convenient than the conventional method, dividing the fracability evaluation grades more specifically. The difference in fracability between samples can be shown intuitively, which enhances the accuracy and reliability of the evaluation of transitional shales and provides theoretical support for reservoir reconstruction.

Description: With the increasing pressure from population growth and economic development, northern China (NC) faces a grand challenge of water scarcity, which can be further exacerbated by climatic and societal changes. The South‐to‐North Water Diversion (SNWD) project is designed to mitigate the water scarcity in NC. However, few studies have quantified the impact of the SNWD on water scarcity within the context of climatic and societal changes and its potential effects on economic and agricultural food in the region. We used water supply stress index (WaSSI) to quantify water scarcity within the context of environmental change in NC, and developed a method to estimate the economic and agricultural impacts of the SNWD. Focuses were put on alleviating the water supply shortage and economic and agricultural benefits for the water‐receiving NC. We find that societal changes, especially economic growth, are the major contributors to water scarcity in NC during 2009–2099. To completely mitigate the water scarcity of NC, at least an additional water supply of 13 billion m3/year (comparable to the annual diversion water by SNWD Central Route) will be necessary. Although SNWD alone cannot provide the full solution to northern China's water shortage in next few decades, it can significantly alleviate the water supply stress in NC (particularly Beijing), considerably increasing the agricultural production (more than 115 Teracalories/year) and bringing economic benefits (more than 51 billion RMB/year) through supplying industrial and domestic water use. Additionally, the transfer project could have impacts on the ecological environment in the exporting regions.

Description: Detecting communities of highly internal and low external interactions in dynamically evolving networks has become increasingly important owing to its wide applications in divers fields. Conventional solutions based on static community detection approaches treat each snapshot of dynamic networks independently, which may fragment communities in time (Aynaud T and Guillaume J L 2010 8th Int. Symp. on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (IEEE) pp 513–9), resulting in the problem of instability. In this work, we develop a novel dynamic community detection algorithm by leveraging the encoding–decoding scheme present in a succinct network representation method to reconstruct each snapshot via a common low-dimensional subspace, which can remove non-significant links and highlight the community structures, resulting in the mitigation of community instability to a large degree. We conduct experiments on simulated data and real social networking data with ground truths (GT) and compare the proposed method with several baselines. Our method is shown to be more stable without missing communities and more effective than the baselines with competitive performance. The distribution of community size in our method is more in line with the real distribution than those of the baselines at the same time.

Description: Background The health impacts of ambient air pollution impose large costs on society. Although all people are exposed to air pollution, the older population (ie, those aged ≥60 years) tends to be disproportionally affected. As a result, there is growing concern about the health impacts of air pollution as many countries undergo rapid population ageing. We investigated the spatial and temporal variation in the economic cost of deaths attributable to ambient air pollution and its interaction with population ageing from 2000 to 2016 at global and regional levels. Methods In this global analysis, we developed an age-adjusted measure of the value of a statistical life-year (VSLY) to estimate the economic cost of deaths attributable to ambient PM2·5 pollution using Global Burden of Diseases, Injuries, and Risk Factors Study 2017 data and country-level socioeconomic information. First, we estimated the global age-specific and cause-specific mortality and years of life lost (YLLs) attributable to PM2·5 pollution using the global exposure mortality model and global estimates of exposure at 0·1° × 0·1° (about 11 km × 11 km at the equator) resolution. Second, for each year between 2000 and 2016, we translated the YLLs within each age group into a health-related cost using a country-specific, age-adjusted measure of VSLY. Third, we decomposed the major driving factors that contributed to the temporal change in health costs related to PM2·5. Finally, we did a sensitivity test to analyse the variability of the estimated health costs to four alternative valuation measures. We identified the uncertainty intervals (UIs) from 1000 draws of the parameters and concentration–response functions by age, cause, country, and year. All economic values are reported in 2011 purchasing power parity-adjusted US dollars. All simulations were done with R, version 3.6.0. Findings Globally, in 2016, PM2·5 was estimated to have caused 8·42 million (95% UI 6·50–10·52) attributable deaths, which was associated with 163·68 million (116·03–219·44) YLLs. In 2016, the global economic cost of deaths attributable to ambient PM2·5 pollution for the older population was US$2·40 trillion (1·89–2·93) accounting for 59% (59–60) of the cost for the total population ($4·09 trillion [3·19–5·05]). The economic cost per capita for the older population was $2739 (2160–3345) in 2016, which was 10 times that of the younger population (ie, those aged 〈60 years). By assessing the factors that contributed to economic costs, we found that increases in these factors changed the total economic cost by 77% for gross domestic product (GDP) per capita, 21% for population ageing, 16% for population growth, −41% for age-specific mortality, and −0·4% for PM2·5 exposure. Interpretation The economic cost of ambient PM2·5 borne by the older population almost doubled between 2000 and 2016, driven primarily by GDP growth, population ageing, and population growth. Compared with younger people, air pollution leads to disproportionately higher health costs among older people, even after accounting for their relatively shorter life expectancy and increased disability. As the world's population is ageing, the disproportionate health cost attributable to ambient PM2·5 pollution potentially widens the health inequities for older people. Countries with severe air pollution and rapid ageing rates need to take immediate actions to improve air quality. In addition, strategies aimed at enhancing health-care services, especially targeting the older population, could be beneficial for reducing the health costs of ambient air pollution.