Search for: All records

Abstract. Aerosol particles are an important part of the Earth climate system, and their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Particles can interact with incoming solar radiation and outgoing longwave radiation, change cloud properties, affect photochemistry, impact surface air quality, change the albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. High particulate matter concentrations at the surface represent an important public health hazard. There are substantial data sets describing aerosol particles in the literature or in public health databases, but they have not been compiled for easy use by the climate and air quality modeling community. Here, we present a new compilation of PM2.5 and PM10 surface observations, including measurements of aerosol composition, focusing on the spatial variability across different observational stations. Climate modelers are constantly looking for multiple independent lines of evidence to verify their models, and in situ surface concentration measurements, taken at the level of human settlement, present a valuable source of information about aerosols and their human impacts complementarily to the column averages or integrals often retrieved from satellites. We demonstrate a method for comparing the data sets to outputs from global climate models that are the basis for projections of future climate and large-scale aerosol transport patterns that influence local air quality. Annual trends and seasonal cycles are discussed briefly and are included in the compilation. Overall, most of the planet or even the land fraction does not have sufficient observations of surface concentrations – and, especially, particle composition – to characterize and understand the current distribution of particles. Climate models without ammonium nitrate aerosols omit ∼ 10 % of the globally averaged surface concentration of aerosol particles in both PM2.5 and PM10 size fractions, with up to 50 % of the surface concentrations not being included in some regions. In these regions, climate model aerosol forcing projections are likely to be incorrect as they do not include important trends in short-lived climate forcers. 

Earth System Models (ESMs) have implemented nitrogen (N) cycles to account for N limitation on terrestrial carbon uptake. However, representing inputs, losses and recycling of N in ESMs is challenging. Here, we use global rates and ratios of key soil N fluxes, including nitrification, denitrification, mineralization, leaching, immobilization and plant uptake (both NH4+ and NO3-), from the literature to evaluate the N cycles in the land model components of two ESMs. The two land models evaluated here, ELMv1-ECA and CLM5.0, originated from a common model but have diverged in their representation of plant/microbe competition for soil N. The models predict similar global rates of gross primary productivity (GPP) but have ~2 to 3-fold differences in their underlying global mineralization, immobilization, plant N uptake, nitrification and denitrification fluxes. Both models dramatically underestimate the immobilization of NO3- by soil bacteria compared to literature values and predict dominance of plant uptake by a single form of mineral nitrogen (NO3- for ELM, with regional exceptions, and NH4+ for CLM5.0). CLM5.0 strongly underestimates the global ratio of gross nitrification:gross mineralization and both models likely substantially underestimate the ratio of nitrification:denitrification. Few experimental data exist to evaluate this last ratio, in part because nitrification and denitrification are quantified with different techniques and because denitrification fluxes are difficult to measure at all. More observational constraints on soil nitrogen fluxes like nitrification and denitrification, as well as greater scrutiny of the functional impact of introducing separate NH4+ and NO3- pools into ESMs, could help improve confidence in present and future simulations of N limitation on the carbon cycle. 

Microbial biomass is known to decrease with soil drying and to increase after rewetting due to physiological assimilation and substrate limitation under fluctuating moisture conditions, but how the effects of moisture changes vary between dry and wet environments is unclear. Here, we conducted a meta‐analysis to assess the effects of elevated and reduced soil moisture on microbial biomass carbon (MBC) and nitrogen (MBN) across a broad range of forest sites between dry and wet regions. We found that the influence of both elevated and reduced soil moisture on MBC and MBN concentrations in forest soils was greater in dry than in wet regions. The influence of altered soil moisture on MBC and MBN concentrations increased significantly with the manipulation intensity but decreased with the length of experimental period, with a dramatic increase observed under a very short‐term precipitation pulse. Moisture effect did not differ between coarse‐ and fine‐textured soils. Precipitation intensity, experimental duration, and site standardized precipitation index (dry or wet climate) were more important than edaphic factors (i.e., initial water content, bulk density, clay content) in determining microbial biomass in response to altered moisture in forest soils. Different responses of microbial biomass in forest soils between dry and wet regions should be incorporated into models to evaluate how changes in the amount, timing and intensity of precipitation affect soil biogeochemical processes.