Organic aerosol (OA) particles affect climate forcing and human health, but their sources and evolution remain poorly characterized. We present a unifying model framework describing the atmospheric evolution of OA that is constrained by high-time-resolution measurements of its composition, volatility, and oxidation state. OA and OA precursor gases evolve by becoming increasingly oxidized, less volatile, and more hygroscopic, leading to the formation of oxygenated organic aerosol (OOA), with concentrations comparable to those of sulfate aerosol throughout the Northern Hemisphere. Our model framework captures the dynamic aging behavior observed in both the atmosphere and laboratory: It can serve as a basis for improving parameterizations in regional and global models.

In this study we compile and present results from the factor analysis of 43 Aerosol Mass Spectrometer (AMS) datasets (27 of the datasets are reanalyzed in this work). The components from all sites, when taken together, provide a holistic overview of Northern Hemisphere organic aerosol (OA) and its evolution in the atmosphere. At most sites, the OA can be separated into oxygenated OA (OOA), hydrocarbon-like OA (HOA), and sometimes other components such as biomass burning OA (BBOA). We focus on the OOA components in this work. In many analyses, the OOA can be further deconvolved into low-volatility OOA (LV-OOA) and semi-volatile OOA (SV-OOA). Differences in the mass spectra of these components are characterized in terms of the two main ions <i>m/z</i> 44 (CO₂⁺) and <i>m/z</i> 43 (mostly C₂H₃O⁺), which are used to develop a new mass spectral diagnostic for following the aging of OA components in the atmosphere. The LV-OOA component spectra have higher <i>f</i>₄₄ (ratio of <i>m/z</i> 44 to total signal in the component mass spectrum) and lower <i>f</i>₄₃ (ratio of <i>m/z</i> 43 to total signal in the component mass spectrum) than SV-OOA. A wide range of <i>f</i>₄₄ and O:C ratios are observed for both LV-OOA (0.17&plusmn;0.04, 0.73&plusmn;0.14) and SV-OOA (0.07&plusmn;0.04, 0.35&plusmn;0.14) components, reflecting the fact that there is a continuum of OOA properties in ambient aerosol. The OOA components (OOA, LV-OOA, and SV-OOA) from all sites cluster within a well-defined triangular region in the <i>f</i>₄₄ vs. <i>f</i>₄₃ space, which can be used as a standardized means for comparing and characterizing any OOA components (laboratory or ambient) observed with the AMS. Examination of the OOA components in this triangular space indicates that OOA component spectra become increasingly similar to each other and to fulvic acid and HULIS sample spectra as <i>f</i>₄₄ (a surrogate for O:C and an indicator of photochemical aging) increases. This indicates that ambient OA converges towards highly aged LV-OOA with atmospheric oxidation. The common features of the transformation between SV-OOA and LV-OOA at multiple sites potentially enable a simplified description of the oxidation of OA in the atmosphere. Comparison of laboratory SOA data with ambient OOA indicates that laboratory SOA are more similar to SV-OOA and rarely become as oxidized as ambient LV-OOA, likely due to the higher loadings employed in the experiments and/or limited oxidant exposure in most chamber experiments

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In order to make the prediction of land surface heat fluxes more robust, two improvements were made to an operational two-layer model proposed previously by Zhang. These improvements are: 1) a surface energy balance method is used to determine the theoretical boundary lines (namely ‘true wet/cool edge’ and ‘true dry/warm edge’ in the trapezoid) in the scatter plot for the surface temperature versus the fractional vegetation cover in mixed pixels; 2) a new assumption that the slope of the Tm – f curves is mainly controlled by soil water content is introduced. The variables required by the improved method include near surface vapor pressure, air temperature, surface resistance, aerodynamic resistance, fractional vegetation cover, surface temperature and net radiation. The model predictions from the improved model were assessed in this study by in situ measurements, which show that the total latent heat flux from the soil and vegetation are in close agreement with the in situ measurement with an RMSE (Root Mean Square Error) ranging from 30 w/m2∼50 w/m2, which is consistent with the site scale measurement of latent heat flux. Because soil evaporation and vegetation transpiration are not measured separately from the field site, in situ measured CO2 flux is used to examine the modeled λEveg. Similar trends of seasonal variations of vegetation were found for the canopy transpiration retrievals and in situ CO2 flux measurements. The above differences are mainly caused by 1) the scale disparity between the field measurement and the MODIS observation; 2) the non-closure problem of the surface energy balance from the surface fluxes observations themselves. The improved method was successfully used to predict the component surface heat fluxes from the soil and vegetation and it provides a promising approach to study the canopy transpiration and the soil evaporation quantitatively during the rapid growing season of winter wheat in northern China.

Abstract1. Bacteria are one of the most abundant and diverse groups of micro-organisms and mediate many critical terrestrial ecosystem processes. Despite the crucial ecological role of bacteria, our understanding of their large-scale biogeography patterns across forests, and the processes that determine these patterns lags significantly behind that of macroorganisms.2. Here, we evaluated the geographic distributions of bacterial diversity and their driving factors across nine latitudinal forests along a 3,700-km north-south transect in eastern China, using high-throughput 16S rRNA gene sequencing.3. Four of 32 phyla detected were dominant: Acidobacteria, Actinobacteria, Alphaproteobacteria and Chloroflexi (relative abundance > 5%). Significant increases in bacterial richness and phylogenetic diversity were observed for temperate forests compared with subtropical or tropical forests. The soil organic matter (SOM) mineralisation rate (SOM min , an index of SOM availability) explained the largest significant variations in bacterial richness. Variation partition analysis revealed that the bacterial community structure was closely correlated with environmental variables and geographic distance, which together explained 80.5% of community variation. Among all environmental factors, climatic features (MAT and MAP) were the best predictors of the bacterial community structure, whereas soil pH and SOM min emerged as the most important edaphic drivers of the bacterial community structure. Plant functional traits (community weighted means of litter N content) and diversity resulted in weak but significant correlations with the bacterial community structure.4. Our findings provide new evidence of bacterial biogeography patterns from tropical to cold temperate forests. Additionally, the results indicated a close linkage among soil bacterial diversity, climate and SOM decomposition, which is critical for

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Background and aims Rhizodeposition of plants is the most uncertain component of the carbon (C) cycle. By existing approaches the amount of rhizodeposition can only roughly be estimated since its persistence in soil is very short compared to other organic C pools. We suggest an approach to quantify rhizodeposition at the field scale by assuming a constant ratio between rhizodeposited-C to root-C. Methods Maize plants were pulse-labeled with 14 CO 2 under controlled conditions and the soil 14 CO 2 efflux was separated into root and rhizomicrobial respiration. The latter and the 14 C activity remaining in the soil corresponded to total rhizodeposition. By relating rhizodeposited-14 C to root-14 C a rhizodeposition-toroot ratio of 0.56 was calculated. This ratio was applied to the root biomass C measured in the field to estimate rhizodeposition under field conditions. Results Maize allocated 298 kg C ha −1 as root-C and 166 kg C ha −1 as rhizodeposited-C belowground, 50 % of which were recovered in the upper 10 cm. The fate of rhizodeposits was estimated based on the 14 C data, which showed that 62 % of total rhizodeposition was mineralized within 16 days, 7 % and 0.3 % was incorporated into microbial biomass and DOC, respectively, and 31 % was recovered in the soil.Conclusions We conclude that the present approach allows for an improved estimation of total rhizodeposition, since it accounts not only for the fraction of rhizodeposits remaining in soil, but also for that decomposed by microorganisms and released from the soil as CO 2 .