The negative effects of PM2.5 concentration in urban development are becoming more and more prominent. Bernaola-Galvan Segmentation Algorithm (BGSA) and wavelet analysis are powerful tools for processing non-linear and non-stationary signals. First, we use BGSA that reveals there are 41 mutation points in the PM2.5 concentration in Guiyang. Then, we reveal the multi-scale evolution of PM2.5 concentration in Guiyang by wavelet analysis. In the first part, we performed one-dimensional continuous wavelet transform (CWT) on the eight monitoring points in the study area, and the results showed that they have obviously similar multi-scale evolution characteristics, with a high-energy and significant oscillation period of 190-512 days. Next, the wavelet transform coherence (WTC) reveals the mutual relationship between the PM2.5 concentration and the atmospheric pollutants and meteorological factors. PM2.5 concentration variation is closely linked to that of PM10 concentration. But, it is not to be ignored that the increase in the SO2 and NO2 concentrations will cause the PM2.5 concentration to rise on different scales. Lastly, the variation of the PM2.5 concentration can be better explained by the combination of multiple factors (2-4) using the multiple-wavelet coherence (MWC). Under the combination of the two factors, the average temperature (Avgtem) and relative humidity (ReH) have the highest AWC and PASC. In the case of the combination of four factors, CO-Avgtem-Wind-ReH plays the largest role in determining PM2.5 concentration.

Soil freeze-thaw cycles play a critical role in ecosystem, hydrological and biogeochemical processes, and climate. The Tibetan Plateau (TP) has the largest area of frozen soil that undergoes freeze-thaw cycles in the low-mid latitudes. Evidence suggests ongoing changes in seasonal freeze-thaw cycles during the past several decades on the TP. However, the status of diurnal freeze-thaw cycles (DFTC) of shallow soil and their response to climate change largely remain unknown. In this study, using in-situ observations, the latest reanalysis, machine learning, and physics-based modeling, we conducted a comprehensive assessment of the spatiotemporal variations of DFTC and their response to climate change in the upper Brahmaputra (UB) basin. About 24 +/- 8% of the basin is subjected to DFTC with a mean frequency of 87 +/- 55 days during 1980-2018. The area and frequency of DFTC show small long-term changes during 1980-2018. Air temperature impacts on the frequency of DFTC changes center mainly around the freezing point (0 degrees C). The spatial variations in the response of DFTC to air temperature can primarily be explained by three factors: precipitation (30.4%), snow depth (22.6%) and seasonal warming/cooling rates (14.9%). Both rainfall and snow events reduce diurnal fluctuations of soil temperature, subsequently reducing DFTC frequency, primarily by decreasing daytime temperature through evaporation-cooling and albedo-cooling effects, respectively. These results provide an in-depth understanding of diurnal soil freeze-thaw status and its response to climate change. Freeze-thaw transitions of terrestrial landscapes are a common phenomenon in cold regions. The seasonal and diurnal freeze-thaw cycles (DFTC) of shallow soil exhibit substantial differences in response to climate. Understanding of the spatiotemporal patterns of DFTC and their response to climate change remains limited over the Tibetan Plateau (TP), which is characterized by the largest areas of freeze-thaw terrain in the mid- and low-latitudes of the world. We found the frequency and area of DFTC show a slight increase trend in a significantly warming climate in upper Brahmaputra (UB) basin, the largest river basin of the TP. The variation of DFTC depends on climatic conditions, with soils near the freezing point (0 degrees C) being more susceptible to changes in DFTC. Precipitation, snow depth and seasonal warming/cooling rates are the top three factors influencing the response of DFTC to air temperature changes. Snowfall plays a more important role in the temporal variability of DFTC frequency than rainfall. The number of diurnal freeze-thaw cycles (DFTC) in shallow soil increase slightly during the period 1980-2018 in the upper Brahmaputra (UB) basin Air temperature effects on the changes in DFTC frequency center on the freezing point Snowfall plays a more important role in the temporal variability of DFTC than rainfall

Atmospheric conditions, topsoil properties and land cover conditions play essential roles in ground surface temperature (GST), surface air temperature (SAT) and their differences (GST-SAT). They determine the strength of the thermal forcing of the lower atmospheric boundary and the distributions of frozen ground in cold regions. However, the relative importance of these factors at various time scales and the underlying physical mechanisms remain less well understood. Here, we investigate the spatiotemporal patterns of GST-SAT and examine 11 potential factors in three categories in influencing the GST-SAT variations from 1983 to 2019 over the Tibetan Plateau (TP) using boosted regression tree models. The results show that the TP has experienced asynchronous warming in GST and SAT since 2001: a warming hiatus in SAT but continued warming in GST, resulting in a significantly increasing trend in GST-SAT. The relative importance of the three categories that influence the GSTSAT spatial variation was: atmospheric variables (56.1 %) > shallow soil properties (24.4 %) > interfacial land cover features (19.5 %). The importance of the factors also varied with the combinations of annual, seasonal, daily, day-time and night-time time scales, manifested by positive or negative effects. The interdecadal changes of net radiation, precipitation, wind speed and soil moisture amplified the asynchronous warming between air and shallow ground over the TP since the 2000s. These findings provide an in-depth understanding of the spatiotemporal variations of GST-SAT and the underlying mechanisms. This study will benefit the development of the Earth system models on the TP.

The Hexi Corridor is an arid region in northwestern China, where hypoliths are widely distributed, resulting from large amounts of translucent stone pavements. In this region, the water and heat distributions are uneven, with a descent gradient from east to west, which can affect the area's biological composition. The impact of environmental heterogeneity on the distribution of hypolithic microbial communities in this area is poorly understood, and this is an ideal location to investigate the factors that may influence the composition and structure of hypolithic microbial communities. An investigation of different sites with differences in precipitation between east and west revealed that the colonization rate decreased from 91.8% to 17.5% in the hypolithic community. Environmental heterogeneity influenced both the structure and function of the hypolithic community, especially total nitrogen (TN) and soil organic carbon (SOC). However, the effect on taxonomic composition was greater than that on ecological function. The dominant bacterial phyla in all sample sites were Cyanobacteria, Actinobacteria, Proteobacteria, and Deinococcus-Thermus, but the abundances varied significantly between the sampling sites. The eastern site had the highest relative abundance of Proteobacteria (18.43%) and Bacteroidetes (6.32%), while the western site had a higher relative abundance in the phyla Cyanobacteria (62%) and Firmicutes (1.45%); the middle site had a higher relative abundance of Chloroflexi (8.02%) and Gemmatimonadetes (1.87%). The dominant phylum in the fungal community is Ascomycota. Pearson correlation analysis showed that the soil's physicochemical properties were also associated with changes in community diversity at the sample sites. These results have important implications for better understanding the community assembly and ecological adaptations of hypolithic microorganisms.

The effects of climate change on permafrost have been well documented in many studies, whereas the effect of climate change on seasonally frozen ground (SFG) is still poorly understood. We used the observed daily freeze depth of SFG and environmental factors data from the period 2007-2016 to examine the seasonal and inter-annual variation of SFG. We quantitatively evaluated the effects of environmental factors on SFG using a boosted regression tree analysis. The results show that, on a seasonal scale, the lower layer soil frost starts freezing in mid-November, with the maximum freeze depth occurring in late March (209 cm), and then begins to thaw in both the lower and upper layers. We identified four stages of the freeze-thaw cycle: the non-frozen phase, initial freezing, deep freezing, and thawing. Furthermore, the thawing process of SFG mainly took place in the upper layer, but the freezing rate of the lower layer from mid-November to early February was similar to the thawing rate of late April to late June. On the inter-annual scale, the maximum freeze depth showed a significant increasing trend (p < 0.05). However, the freeze-thaw duration declined significantly (p < 0.05), which was correlated with the decrease in the period when surface soil temperature is below 0 degrees C. The mean soil temperature and soil heat flux were the most important environmental indicators affecting seasonal variation of SFG depth, and the cumulative negative air and soil temperatures were the dominant factors affecting inter-annual variation of maximum freeze depth. Our results might provide insight into predicting hydrological and ecological responses to future climate change in frozen-ground regions.

Changes in the freeze-thaw cycles of shallow soil have important consequences for surface and subsurface hydrology, land-atmosphere energy and moisture interaction, carbon exchange, and ecosystem diversity and productivity. This work examines the shallow soil freeze-thaw cycle on the Tibetan Plateau (TP) using in-situ soil temperature observations in 0-20 cm soil layer during July 1982-June 2017. The domain and layer averaged beginning frozen day is November 18 and delays by 2.2 days per decade; the ending frozen day is March 9 and advances by 3.2 days per decade; the number of frozen days is 109 and shortens by 5.2 days per decade. Altitude and latitude combined could explain the spatial patterns of annual mean freeze-thaw status well. Stations located near 0 degrees C contour line experienced dramatic changes in freeze-thaw cycles as seen from subtropical mountain coniferous forest in the southern TP. Soil completely freezes from surface to 20-cm depth in 15 days while completely thaws in 10 days on average. Near-surface soil displays more pronounced changes than deeper soil. Surface air temperature strongly influences the shallow soil freeze-thaw status but snow exerts limited effects. Different thresholds in freeze-thaw status definition lead to differences in the shallow soil freeze-thaw status and multiple-consecutive-day approach appears to be more robust and reliable. Gridded soil temperature products could resolve the spatial pattern of the observed shallow soil freeze-thaw status to some extent but further improvement is needed.

The Nanwenghe Wetlands Reserve in the Yile'huli Mountains is a representative region of the Xing'an permafrost. The response of permafrost to climate change remains unclear due to limited field investigations. Thus, longer-term responses of the ground thermal state to climate change since 2011 have been monitored at four sites with varied surface characteristics: Carex tato wetland (P1) and shrub-C. tato wetland (P2) with a multi-year average temperatures at the depth of zero annual amplitude (T-ZAA) of -0.52 and -1.19 degrees C, respectively; Betula platyphylla-Larix gmelinii (Rupr.) Kuzen mixed forest (P3) with T-ZAA of 0.17 degrees C, and; the forest of L. gmelinii (Rupr.) Kuzen (P4) with T-ZAA of 1.65 degrees C. Continuous observations demonstrate that the ecosystem-protected Xing'an permafrost experienced a cooling under a warming climate. The temperature at the top of permafrost (TTOP) rose (1.8 degrees C per decade) but the T-ZAA declined (-0.14 degrees C per decade), while the active layer thickness (ALT) thinned from 0.9 m in 2012 to 0.8 m in 2014 at P1. Both the TTOP and T-ZAA increased (0.89 and 0.06 degrees C per decade, respectively), but the ALT thinned from 1.4 m in 2012 to 0.7 m in 2016 at P2. Vertically detached permafrost at P3 disappeared in summer 2012, with warming rates of +0.42 and + 0.17 degrees C per decade for TTOP and T-ZAA, respectively. However, up to date, the ground thermal state has remained stable at P4. We conclude that the thermal offset is crucial for the preservation and persistence of the Xing'an permafrost at the southern fringe.

The largest permafrost area in China is on the Qinghai-Tibetan Plateau (QTP), and the nitrogen biogeochemical cycles in this area have received significant attention. However, there is insufficient knowledge of the available soil nitrogen and microbial biomass nitrogen (MBN) dynamics in this region, which hinders our understanding of the changes in the ecosystem and the effects of climate change on the nitrogen dynamics in the future. In this study, we determined the monthly changes in ammonium nitrogen, nitrate nitrogen, dissolved organic nitrogen (DON), and MBN contents of the topsoil (at depths of 0-20 cm) from April 2016 to March 2017 in the permafrost region on the QTP. The results show that soil NH4+-N and DON contents decreased during the growing season, while soil NO3--N content increased during the growing season and in the middle of the winter. The soil MBN contents increased at the beginning of the growing season and decreased during peak growth period, despite significant variations among the different sites. The soil temperature was positively correlated with soil NO3--N content but it was negatively correlated with the NH4+-N and DON contents. The soil moisture was positively correlated with the soil NO3--N, DON, and MBN contents. The primary factor affecting the seasonal patterns in soil NO3--N and DON contents was soil moisture. Soil moisture and plant growth also affected soil MBN via nutrient competition. The nutrient uptake by plants overwhelmed effect of temperature on the MBN in growing season. These findings improve our understanding of the nitrogen biochemical cycles and their response to future climate change.

The largest permafrost area in China is on the Qinghai-Tibetan Plateau (QTP), and the nitrogen biogeochemical cycles in this area have received significant attention. However, there is insufficient knowledge of the available soil nitrogen and microbial biomass nitrogen (MBN) dynamics in this region, which hinders our understanding of the changes in the ecosystem and the effects of climate change on the nitrogen dynamics in the future. In this study, we determined the monthly changes in ammonium nitrogen, nitrate nitrogen, dissolved organic nitrogen (DON), and MBN contents of the topsoil (at depths of 0-20 cm) from April 2016 to March 2017 in the permafrost region on the QTP. The results show that soil NH4+-N and DON contents decreased during the growing season, while soil NO3--N content increased during the growing season and in the middle of the winter. The soil MBN contents increased at the beginning of the growing season and decreased during peak growth period, despite significant variations among the different sites. The soil temperature was positively correlated with soil NO3--N content but it was negatively correlated with the NH4+-N and DON contents. The soil moisture was positively correlated with the soil NO3--N, DON, and MBN contents. The primary factor affecting the seasonal patterns in soil NO3--N and DON contents was soil moisture. Soil moisture and plant growth also affected soil MBN via nutrient competition. The nutrient uptake by plants overwhelmed effect of temperature on the MBN in growing season. These findings improve our understanding of the nitrogen biochemical cycles and their response to future climate change.

In this study, the spatiotemporal changes in net primary production (NPP) and drivers, including climate change, atmospheric CO2 concentration and land use change, over the Tibetan Plateau from 1979 to 2016 were investigated using the version 4.5 of the Community Land Model. Based on high-resolution atmospheric forcing data, six numerical experiments were designed to assess the relative contribution of different environmental factors on NPP. Our simulation results suggest that NPP over the Tibetan Plateau has increased significantly at a rate of 2.25TgC/year(2) since 1979. At the plateau scale, changes in precipitation, CO2 concentration, and land use change contributed approximately 63.3%, 16.7%, and 9.5% to the interannual variation of NPP, respectively. Temperature did not exert a significant effect on the trends of NPP, which results from the increasing temperature enhancing the autotrophic respiration (AR) more than the gross primary production. We also divided the alpine grasslands into four types, including alpine meadow of permafrost, alpine steppe of permafrost, alpine meadow of seasonal frost, and alpine steppe of seasonal frost. We found that the increasing rate of NPP in permafrost regions was significantly higher than that in seasonal frost regions. Compared with other factors, precipitation change played a dominant role in the NPP over the four different types of grasslands. Temperature-induced change on NPP and AR was larger in the alpine meadow regions compared to in the alpine steppe regions. In addition, NPP and AR showed a more remarkable response to temperature change over alpine meadow of permafrost than other regions.