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.

Freeze-thaw (FT) events profoundly perturb the biochemical processes of soil and water in mid- and high-latitude regions, especially the riparian zones that are often recognized as the hotspots of soil-water interactions and thus one of the most sensitive ecosystems to future climate change. However, it remains largely unknown how the heterogeneously composed and progressively discharged meltwater affect the biochemical cycling of the neighbor soil. In this study, stream water from a valley in the Chinese Loess Plateau was frozen at -10 degrees C for 12 hours, and the meltwater (at +10 degrees C) progressively discharged at three stages (T1 similar to T3) was respectively added to rewet the soil collected from the same stream bed (Soil+T1 similar to Soil+T3). Our results show that: (1) Approximately 65% of the total dissolved organic carbon and 53% of the total NO3--N were preferentially discharged at the first stage T1, with enrichment ratios of 1.60 similar to 1.94. (2) The dissolved organic matter discharged at T1 was noticeably more biodegradable with significantly lower SUVA(254) but higher HIX, and also predominated with humic-like, dissolved microbial metabolite-like, and fulvic acid-like components. (3) After added to the soil, the meltwater discharged at T1 (e.g., Soil+T1) significantly accelerated the mineralization of soil organic carbon with 2.4 similar to 8.07-folded k factor after fitted into the first-order kinetics equation, triggering 125 similar to 152% more total CO2 emissions. Adding T1 also promoted significantly more accumulation of soil microbial biomass carbon after 15 days of incubation, especially on the FT soil. Overall, the preferential discharge of the nutrient-enriched meltwater with more biodegradable DOM components at the initial melting stage significantly promoted the microbial growth and respiratory activities in the recipient soil, and triggered sizable CO2 emission pulses. This reveals a common but long-ignored phenomenon in cold riparian zones, where progressive freeze-thaw can partition and thus shift the DOM compositions in stream water over melting time, and in turn profoundly perturb the biochemical cycles of the neighbor soil body.

Brown carbon (BrC) has been recognized as an important light-absorbing carbonaceous aerosol, yet understanding of its influence on regional climate and air quality has been lacking, mainly due to the ignorance of regional coupled meteorology-chemistry models. Besides, assumptions about its emissions in previous explorations might cause large uncertainties in estimates. Here, we implemented a BrC module into the WRF-Chem model that considers source-dependent absorption and avoids uncertainties caused by assumptions about emission intensities. To our best knowledge, we made the first effort to consider BrC in a regional coupled model. We then applied the developed model to explore the impacts of BrC absorption on radiative forcing, regional climate, and air quality in East Asia. We found notable increases in aerosol absorption optical depth (AAOD) in areas with high OC concentrations. The most intense forcing of BrC absorption occurs in autumn over Southeast Asia, and values could reach around 4 W m(-2). The intensified atmospheric absorption modified surface energy balance, resulting in subsequent declines in surface temperature, heat flux, boundary layer height, and turbulence exchanging rates. These changes in meteorological variables additionally modified near-surface dispersion and photochemical conditions, leading to changes of PM2.5 and O-3 concentrations. These findings indicate that BrC could exert important influence in specific regions and time periods. A more in-depth understanding could be achieved later with the developed model.

China experiences severe particulate matter (PM) pollution. Although a monitoring network for PM2.5 (diameter < 2.5 mu m) has been set up in more than 100 major Chinese cities, insufficient spatial coverage of observations limits the study of the temporal and spatial characteristics, influencing factors, and component of PM2.5. In this study, we conducted a one year air quality simulation using a regional climate-chemistry model and evaluated the simulation's performance based on in situ observations concerning meteorological elements and PM2.5 concentrations. The simulated results showed that, higher PM2.5 concentrations appeared in northern China and the Sichuan Basin, and the maximal value occurred in winter. Furthermore, Vertical PM2.5 concentrations presented a gradual decreasing trend from the surface, whereas in southern coastal cities the profiles were unsteady with a secondary peak in the lower layer. Meteorological conditions were conducive to both pollutant diffusion and removal in summer, whereas stagnant conditions appeared in winter, characterized by high sea level pressure (SLP), the lowest planetary boundary layer height (PBLH), and 2-m temperature (T2). In provincial capital cities, PM2.5 was positively correlated with residential emissions but negatively correlated with precipitation, 10-m wind speed, T2, PBLH, and industrial emissions. Finally, we utilized the simulation results to investigate the component variations of PM2.5. Results indicated that primary PM2.5 components had significantly higher concentrations in northern China where residential heating is the major source of PM2.5 emissions, whereas they had lower concentrations in southern China. Secondary components played a crucial role in PM2.5 mass in eastern China. This study provided a clear perspective of seasonal variations, horizontal and vertical distributions of PM2.5 and its components and influence factors, which could be used in subsequent studies to investigate the formation mechanism and emission sources of PM2.5.

PM2.5 impacts the atmospheric temperature structure through scattering or absorbing solar radiation, whose concentration and composition can affect the impact. This study calculated the effect of PM2.5 on the temperature structures in the urban centre and the suburbs of Nanjing, as well as their differences. The results show that the optical parameters, atmospheric heating rate, radiative forcing, and temperature are all impacted by the concentration and composition of PM2.5. The uneven distribution of PM2.5 influences the differences in those factors between the urban centre and suburbs. In spring, summer, autumn, and winter, surface temperatures in the urban centre were approximately 283 K, 285 K, 305 K, and 277 K, while those in the suburbs were approximately 282 K, 283 K, 304 K, and 274 K. The urban heat island intensity has been reduced by 0.1-0.4 K due to the presence of PM2.5 in Nanjing. Due to the black carbon component's warming effect on the top of the boundary layer, the impact of PM2.5 on the urban heat island intensity profile drops quickly at the 0.75-1.25 km. PM2.5 may mask the warm city problem and have a more complex impact on the urban climate.

A number of global surface soil moisture (SM) datasets have been retrieved from the L-band frequency Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) missions to study the terrestrial water, energy, and carbon cycles. This paper presents the performance of the recently developed 9 km global SMAP product (hereafter SMAP-INRAE-BORDEAUX, SMAP-IB9). The product retrieves SM from the 9 km SMAP radiometric products using the forward model (L-MEB, L-band Microwave Emission of the Biosphere) of SMOS INRA-CESBIO (SMOS-IC) and SMOS L2 algorithms. We inter-compared SMAP-IB9 with two other products with a similar grid resolution (similar to 10 km): the SMAP Enhanced Level-3 SM dataset (SMAP-E) and the enhanced global dataset for the land component of the fifth generation of European reanalysis (ERA5-Land) with the main objective of assessing the discrepancy in accuracy between remotely sensed and model SM datasets. We found that ERA5-Land and SMAP-IB9 SM had the overall highest correlations (R = 0.62(+/- 0.15) for ERA5-Land vs. 0.60 (+/- 0.17) for SMAP-IB9 and 0.50(+/- 0.15) for SMAP-E) by comparing with the International Soil Moisture Network (ISMN) in-situ measurements from 22 networks. ERA5-Land showed better performances in the forest areas where SMAP-IB9 and SMAP-E still showed high potential in detecting the time variations of the observed SM, particularly in terms of median correlation values (0.62(+/- 0.18) for SMAP-IB9 vs. 0.66(+/- 0.16) for ERA5-and). The discrepancy in R between satellite and model SM products that were reported in some past studies has decreased to statistically insignificant levels over time. For instance, in the non-forest areas, we found that the latest versions of the SMAP SM products (SMAP-E and SMAP-IB9) had relatively comparable performances with ERA5-Land with regard to median ubRMSE (0.07(+/- 0.02) m(3)/m(3) for both SMAP-E and ERA5-Land) and R (0.59 (+/- 0.16) for SMAP-IB9 vs. 0.61(+/- 0.15) for ERA5-Land), respectively.

Europe has experienced many extreme heat waves over the past few decades. In this study, the physical processes underlying these long-lasting and wide-ranging heat wave events are investigated based on a case study in Europe in June 2021. Heat waves are associated with barotropic anticyclonic anomalies accompanied by positive geopotential height anomalies locally. These anomalies persist under the conditions of increased meridional air temperature gradients of the mid-upper troposphere in the high latitudes of Eurasia and the formation of the Arctic front jet. The shrinking high-latitude snow cover in April-May favors higher surface temperatures and larger meridional temperature gradients in June in the mid-upper troposphere due to the soil moisture-evaporation-temperature positive feedback process. The summer Arctic front jet is then strengthened, and the mid-latitude westerly winds are weakened. This atmospheric circulation background favors waveguide formation and wave resonance that produces high-amplitude atmospheric waves and the stagnation of ridges in the midlatitudes. Numerical experiments using the Community Atmosphere Model version 5 verify the proposed physical mechanisms, with the climatic responses in sensitivity experiments to anomalous snowfall rates closely resembling the observational results. Therefore, in June 2021, under the identified atmospheric circulation background and the perturbation of the upstream positive phase of the North Atlantic Oscillation, the large-scale barotropic high pressure and barotropic anticyclonic circulation in the study region tended to be stable and persistent, which is favorable for the production of long-lasting and wide-ranging heat wave events.

Air pollutants can be transported to the pristine regions such as the Tibetan Plateau, by monsoon and stratospheric intrusion. The Tibetan Plateau region has limited local anthropogenic emissions, while this region is influenced strongly by transport of heavy emissions mainly from South Asia. We conducted a comprehensive study on various air pollutants (PM2.5, total gaseous mercury, and surface ozone) at Nam Co Station in the inland Tibetan Plateau. Monthly mean PM2.5 concentration at Nam Co peaked in April before monsoon season, and decreased during the whole monsoon season (June-September). Monthly mean total gaseous mercury concentrations at Nam Co peaked in July and were in high levels during monsoon season. The Indian summer monsoon acted as a facilitator for transporting gaseous pollutants (total gaseous mercury) but a suppressor for particulate pollutants (PM2.5) during the monsoon season. Different from both PM2.5 and total gaseous mercury variabilities, surface ozone concentrations at Nam Co are primarily attributed to stratospheric intrusion of ozone and peaked in May. The effects of the Indian summer monsoon and stratospheric intrusion on air pollutants in the inland Tibetan Plateau are complex and require further studies. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.

The Granger Causality (GC) statistical test explores the causal relationships between different time series variables. By employing the GC method, the underlying causal links between environmental drivers and global vegetation properties can be untangled, which opens possibilities to forecast the increasing strain on ecosystems by droughts, global warming, and climate change. This study aimed to quantify the spatial distribution of four distinct satellite vegetation products' (VPs) sensitivities to four environmental land variables (ELVs) at the global scale given the GC method. The GC analysis assessed the spatially explicit response of the VPs: (i) the fraction of absorbed photosynthetically active radiation (FAPAR), (ii) the leaf area index (LAI), (iii) solar-induced fluorescence (SIF), and, finally, (iv) the normalized difference vegetation index (NDVI) to the ELVs. These ELVs can be categorized as water availability assessing root zone soil moisture (SM) and accumulated precipitation (P), as well as, energy availability considering the effect of air temperature (T) and solar shortwave (R) radiation. The results indicate SM and P are key drivers, particularly causing changes in the LAI. SM alone accounts for 43%, while P accounts for 41%, of the explicitly caused areas over arid biomes. SM further significantly influences the LAI at northern latitudes, covering 44% of cold and 50% of polar biome areas. These areas exhibit a predominant response to R, which is a possible trigger for snowmelt, showing more than 40% caused by both cold and polar biomes for all VPs. Finally, T's causality is evenly distributed amongst all biomes with fractional covers between similar to 10 and 20%. By using the GC method, the analysis presents a novel way to monitor the planet's ecosystem, based on solely two years as input data, with four VPs acquired by the synergy of Sentinel-3 (S3) and 5P (S5P) satellite data streams. The findings indicated unique, biome-specific responses of vegetation to distinct environmental drivers.

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM2.5, PM10, SO2, NO2, CO, and O-3 concentrations ranged from 51.44 to 59.54 mu g m(-3), 128.43-155.28 mu g m(-3), 10.99-17.99 mu g m(-3), 26.27-31.71 mu g m(-3), 1.04-1.32 mg m(-3), and 55.27-65.26 mu g m(-3), respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM2.5/PM10 ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM2.5 (PM10) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. similar to 5-6 (similar to 7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM2.5 (PM10) concentrations similar to 8-54 (similar to 26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4 mg m(-3). Such high PM2.5 and concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region. (C) 2020 Elsevier Ltd. All rights reserved.