Aerosols are an important factor leading to reduced visibility. In order to better comprehend the connection between visibility and aerosols, aerosol optical depth (AOD) and Angstrom exponent (AE) data from the Himawari-8 Advanced Himawari Imager (AHI) are used for validation in comparison with the data from the Aerosol Robotic Network (AERONET) observations in this paper, which amounted to 69,026 sets of data. The results indicate that the AOD of AHI is in good agreement with AERONET observations, but AE performs poorly. The correlation coefficients between the AOD of AHI and AERONET data increase with decreasing visibility and the root mean square error increase. The AE of AHI performs poorly in different visibility conditions. The conclusion drawn from further analysis of the correlation between aerosol products and meteorological factors is that the factor with the highest correlation with visibility. Mixed aerosols dominate at higher visibility and biomass burning/urban-industrial aerosols dominate at lower visibility. The visibility in a typical city (Beijing) has a strong negative correlation with AOD, a weak negative correlation with AE, and a strong correlation with aerosol radiative forcing. The reduction in visibility may be caused by the scattering and adsorption effects of aerosols. The results are important for the improvement and application of AHI aerosol products in regional pollution studies.

An effective production structure of economic sectors may play an important role in balancing societal advances and environmental conservation, which are two competing sustainable development objectives. We tested the notion in the context of Tibet region. The region is considered to be a critical barrier for ecological security in China, whereas its environment is largely impacted by economic development that is dominated by major regional cities like Lhasa. To understand what the overall role of economic structures prevailed by major cities may play in the balancing act, we integrate a complex network with an input-output (IO) table from regional perspectives, to delineate the sector-based production and unravel more about the core sectors that drove the overall economic production from 2012 to 2107 in Tibet. We found that there was a significant influence of public administration and social security sector on production, but economy was largely contributed by primary and construction sectors, which highly depended on natural resource consumption. However, the production structure was undergoing a shift, largely reflected by the changes of the core sectors, which started leaning to service sectors with relatively higher productivity and lower environmental impacts. Meanwhile, it highlighted the challenges to sustain the economy without more withdrawal of natural resources, consequently towards more balanced development. Therefore, based on key production path assessment, we further put forward pathways towards more sustainable development by improving supply chain that is centered in agriculture, while transforming sectors around green manufacturing and shifting to more robust and productive service sectors.

Under the background of climate change, freeze-thaw patterns tend to be turbulent: ecosystem function processes and their mutual feedback mechanisms with microorganisms in sensitive areas around the world are currently a hot topic of research. We studied changes of soil properties in alpine wetlands located in arid areas of Central Asia during the seasonal freeze-thaw period (which included an initial freezing period, a deep freezing period, and a thawing period), and analyzed changes in soil bacterial community diversity, structure, network in different stages with the help of high-throughput sequencing technology. The results showed that the alpha diversity of the soil bacterial community showed a continuous decreasing trend during the seasonal freeze-thaw period. The relative abundance of dominant bacterial groups (Proteobacteria (39.04%-41.28%) and Bacteroidota (14.61%-20.12%)) did not change significantly during the freeze-thaw period. At the genus level, different genera belonging to the same phylum dominated in different stages, or there were clusters of genera belonging to different phylum. For example, g_Ellin6067, g_unclassified_f_Geobacteraceae, g_unclassified_f_Gemmatimonadaceae coexisted in the same cluster, belonging to Proteobacteria, Desulfobacterota and Gemmatimonadota respectively, and their abundance increased significantly during the freezing period. This adaptive freeze-thaw phylogenetic model suggests a heterogeneous stress resistance of bacteria during the freeze-thaw period. In addition, network analysis showed that, although the bacterial network was affected to some extent by environmental changes during the initial freezing period and its recovery in the thawing period lagged behind, the network complexity and stability did not change much as a whole. Our results prove that soil bacterial communities in alpine wetlands are highly resistant and adaptive to seasonal freeze-thaw conditions. As far as we know, compared with short-term freeze-thaw cycles research, this is the first study examining the influence of seasonal freeze-thaw on soil bacterial communities in alpine wetlands. Overall, our findings provide a solid base for further investigations of biogeochemical cycle processes under future climate change.

Permafrost active layer soils are harsh environments with thaw/freeze cycles and sub-zero temperatures, harboring diverse microorganisms. However, the distribution patterns, assembly mechanism, and driving forces of soil microeukaryotes in permafrost remain largely unknown. In this study, we investigated microeukaryotes in permafrost active layer across the Qinghai-Tibet Plateau (QTP) using 18S rRNA gene sequencing. The results showed that the microbial eukaryotic communities were dominated by Nematozoa, Ciliophora, Ascomycota, Cercozoa, Arthropoda, and Basidiomycota in terms of relative abundance and operational taxonomic unit (OTU) richness. Nematozoa had the highest relative abundance, while Ciliophora had the highest OTU richness. These phyla had strong interactions between each other. Their alpha diversity and community structure were differently influenced by the factors associated to location, climate, and soil properties, particularly the soil properties. Significant but weak distance-decay relationships with different slopes were established for the communities of these dominant phyla, except for Basidiomycota. According to the null model, community assemblies of Nematozoa and Cercozoa were dominated by heterogeneous selection, Ciliophora and Ascomycota were dominated by dispersal limitation, while Arthropoda and Basidiomycota were highly dominated by non-dominant processes. The assembly mechanisms can be jointly explained by biotic interactions, organism treats, and environmental influences. Modules in the co-occurrence network of the microeukaryotes were composed by members from different taxonomic groups. These modules also had interactions and responded to different environmental factors, within which, soil properties had strong influences on these modules. The results suggested the importance of biological interactions and soil properties in structuring microbial eukaryotic communities in permafrost active layer soil across the QTP.

Large amounts of carbon sequestered in permafrost on the Tibetan Plateau (TP) are becoming vulnerable to microbial decomposition in a warming world. However, knowledge about how the responsible microbial community responds to warming-induced permafrost thaw on the TP is still limited. This study aimed to conduct a comprehensive comparison of the microbial communities and their functional potential in the active layer of thawing permafrost on the TP. We found that the microbial communities were diverse and varied across soil profiles. The microbial diversity declined and the relative abundance of Chloroflexi, Bacteroidetes, Euryarchaeota, and Bathyarchaeota significantly increased with permafrost thawing. Moreover, warming reduced the similarity and stability of active layer microbial communities. The high-throughput qPCR results showed that the abundance of functional genes involved in liable carbon degradation and methanogenesis increased with permafrost thawing. Notably, the significantly increased mcrA gene abundance and the higher methanogens to methanotrophs ratio implied enhanced methanogenic activities during permafrost thawing. Overall, the composition and functional potentials of the active layer microbial community in the Tibetan permafrost region are susceptible to warming. These changes in the responsible microbial community may accelerate carbon degradation, particularly in the methane releases from alpine permafrost ecosystems on the TP. Warming-induced permafrost thawing increased the abundance of anaerobic microorganisms and functional genes involved in labile carbon degradation and methane cycles, which could accelerate soil carbon degradation on TP.

Microbes are a critical component of soil ecosystems, performing crucial functions in biogeochemical cycling, carbon sequestration, and plant health. However, it remains uncertain how their community structure, functioning, and resul-tant nutrient cycling, including net GHG fluxes, would respond to climate change at different scales. Here, we review global and regional climate change effects on soil microbial community structure and functioning, as well as the climate-microbe feedback and plant-microbe interactions. We also synthesize recent studies on climate change impacts on terrestrial nutrient cycles and GHG fluxes across different climate-sensitive ecosystems. It is generally assumed that climate change factors (e.g., elevated CO2 and temperature) will have varying impacts on the microbial community structure (e.g., fungi-to-bacteria ratio) and their contribution toward nutrient turnover, with potential interactions that may either enhance or mitigate each other's effects. Such climate change responses, however, are difficult to gen-eralize, even within an ecosystem, since they are subjected to not only a strong regional influence of current ambient environmental and edaphic conditions, historical exposure to fluctuations, and time horizon but also to methodolog-ical choices (e.g., network construction). Finally, the potential of chemical intrusions and emerging tools, such as ge-netically engineered plants and microbes, as mitigation strategies against global change impacts, particularly for agroecosystems, is presented. In a rapidly evolving field, this review identifies the knowledge gaps complicating assessments and predictions of microbial climate responses and hindering the development of effective mitigation strategies.

Using the coupled coordination degree model, DEA coupled coordination efficiency model, and spatial autocorrelation model, this study explored the dynamic coupled coordination relationship and spatial correlation between the ice-snow tourism network attention and tourism industry development in 31 Chinese provinces and proposed suggestions pertaining to development. Our findings showed that (1) most provinces have not yet achieved excellent coordinated development between the two systems, and the coupled coordination efficiency is low. Each province's coupled coordination degree and coordination efficiency exhibited a small increase. (2) Spatial differences in the coupled coordination level and coordination efficiency of the two systems in each province were more evident. In seven provinces, including Heilongjiang, tourism industry development demonstrated a relatively high utilization rate and enhanced ice-snow tourism network attention. (3) The rankings of the coupled coordination degree and coordination efficiency of the two systems in each province remained relatively stable at the upper and lower ends, with large changes in the central provinces. The coupled coordination efficiency of Heilongjiang, Beijing, Jilin, and Shanghai remained at the top of the list steadily, whereas Tibet, Anhui, and Qinghai stayed at the bottom. In contrast, the ranking of the coupled coordination efficiency of Inner Mongolia, Henan, and Jiangsu displayed a great change. (4) The spatial correlation analysis revealed a positive correlation that decreased annually. Some provinces exhibited characteristics of spatial aggregation, with a high-high aggregation effect in Liaoning and Jilin, a low-low aggregation effect in Gansu and Qinghai, and no spatial aggregation effect in most other provinces.

It is proposed to build a high-speed railway through the China -Mongolia -Russia economic corridor (CMREC) which runs from Beijing to Moscow via Mongolia. However, the frozen ground in this corridor has great impacts on the infrastructure stability, especially under the background of climate warming and permafrost degradation. Based on the Bayesian Network Model (BNM), this study evaluates the suitability for engineering construction in the CMREC, by using 21 factors in five aspects of terrain, climate, ecology, soil, and frozen-ground thermal stability. The results showed that the corridor of Mongolia's Gobi and Inner Mongolia in China is suitable for engineering construction, and the corridor in Amur, Russia near the northern part of Northeast China is also suitable due to cold and stable permafrost overlaying by a thin active layer. However, the corridor near Petropavlovsk in Kazakhstan and Omsk in Russia is not suitable for engineering construction because of low freezing index and ecological vulnerability. Furthermore, the sensitivity analysis of influence factors indicates that the thermal stability of frozen ground has the greatest impact on the suitability of engineering construction. These conclusions can provide a reference basis for the future engineering planning, construction and risk assessment.

Aviation emissions are the only direct source of anthropogenic particulate pollution at high altitudes, which can form con-trails and contrail-induced clouds, with consequent effects upon global radiative forcing. In this study, we develop a pre-dictive model, called APMEP-CNN, for aviation non-volatile particulate matter (nvPM) emissions using a convolutional neural network (CNN) technique. The model is established with data sets from the newly published aviation emission databank and measurement results from several field studies on the ground and during cruise operation. The model also takes the influence of sustainable aviation fuels (SAFs) on nvPM emissions into account by considering fuel properties. This study demonstrates that the APMEP-CNN can predict nvPM emission index in mass (EIm) and number (EIn) for a number of high-bypass turbofan engines. The accuracy of predicting EIm and EIn at ground level is significantly improved (R2 = 0.96 and 0.96) compared to the published models. We verify the suitability and the applicability of the APMEP-CNN model for estimating nvPM emissions at cruise and burning SAFs and blend fuels, and find that our predictions for EIm are within & PLUSMN;36.4 % of the measurements at cruise and within & PLUSMN;33.0 % of the measurements burning SAFs in av-erage. In the worst case, the APMEP-CNN prediction is different by -69.2 % from the measurements at cruise for the JT3D-3B engine. Thus, the APMEP-CNN model can provide new data for establishing accurate emission inventories of global aviation and help assess the impact of aviation emissions on human health, environment and climate.Synopsis: The results of this paper provide accurate predictions of nvPM emissions from in-use aircraft engines, which im-pact airport local air quality and global radiative forcing.

Global climate change has altered soil freeze-thaw (FT) patterns but less is known about the responses of soil microbial diversity, soil multifunctionality, and their relationship to FT events. Daxing'an Mountains in China, located in high-latitude permafrost ecosystems, are one of the most sensitive areas to climate change and FT patterns. Here, simulated FT conditions were used to determine the impact of FT events on soil microbial diversity and multifunctionality as well as to elucidate the relationships between bacterial and fungal diversity and multifunctionality. Community composition, alpha-diversity index, and co-occurrence network complexity of fungi significantly changed during FT events, whereas the same parameters did not exhibit significant alterations for bacteria. Soil fungal communities were more sensitive to FT events than soil bacterial communities. FT events significantly affected soil multifunctionality. A random forest analysis showed that the fungal diversity index was the main predictor of soil multifunctionality. Moreover, changes in soil abiotic factors also affected the relationship between soil microbial diversity and multifunctionality. Soil multifunctionality was also constrained by fungal community network complexity. Structural equation model showed that the FT amplitude and FT cycles exerted different impact paths on soil multifunctionality. The effect of FT cycles on soil multifunctionality (0.289) was greater than that of FT amplitude (0.080). As global climate change is expected to accelerate in the future, extension of the FT period in high-altitude and high-latitude regions may have a severe impact on soil function compared to extreme low temperatures caused by the presence of thin snow cover.