Ozone deposition impact assessments for forest canopies require accurate ozone flux partitioning on diurnal timescales

Dry deposition is an important sink of tropospheric ozone that affects surface concentrations and impacts crop yields, the land carbon sink, and the terrestrial water cycle. Dry deposition pathways include plant uptake via stomata and non-stomatal removal by soils, leaf surfaces, and chemical reactions. Observational studies indicate that ozone deposition exhibits substantial temporal variability that is not reproduced by atmospheric chemistry models due to a simplified representation of vegetation uptake processes in these models. In this study, we explore the importance of stomatal and non-stomatal uptake processes in driving ozone dry deposition variability on diurnal to seasonal timescales. Specifically, we compare two land surface ozone uptake parameterizations - a commonly applied big leaf parameterization (W89; Wesely, 1989) and a multi-layer model (MLC-CHEM) constrained with observations - to multi-year ozone flux observations at two European measurement sites (Ispra, Italy, and Hyytiala, Finland). We find that W89 cannot reproduce the diurnal cycle in ozone deposition due to a misrepresentation of stomatal and non-stomatal sinks at our two study sites, while MLC-CHEM accurately reproduces the different sink pathways. Evaluation of non-stomatal uptake further corroborates the previously found important roles of wet leaf uptake in the morning under humid conditions and soil uptake during warm conditions. The misrepresentation of stomatal versus non-stomatal uptake in W89 results in an overestimation of growing season cumulative ozone uptake (CUO), a metric for assessments of vegetation ozone damage, by 18 % (Ispra) and 28 % (Hyytiala), while MLC-CHEM reproduces CUO within 7 % of the observation-inferred values. Our results indicate the need to accurately describe the partitioning of the ozone atmosphere-biosphere flux over the in-canopy stomatal and non-stomatal loss pathways to provide more confidence in atmospheric chemistry model simulations of surface ozone mixing ratios and deposition fluxes for large-scale vegetation ozone impact assessments.Peer reviewe

What chemical species are responsible for new particle formation and growth in the Netherlands? A hybrid positive matrix factorization (PMF) analysis using aerosol composition (ACSM) and size (SMPS)

Aerosol formation acts as a sink for gas-phase atmospheric species that controls their atmospheric lifetime and environmental effects. To investigate aerosol formation and evolution in the Netherlands, a hybrid positive matrix factorization (PMF) analysis was conducted using observations from May, June, and September 2021 collected in the rural site of Cabauw in the central part of the Netherlands. The hybrid input matrix consists of the full organic mass spectrum acquired from a time-of-flight aerosol chemical speciation monitor (ToF-ACSM), ACSM inorganic species concentrations, and binned particle size distribution concentrations from a scanning mobility particle sizer (SMPS). These hybrid PMF analyses discerned four factors that describe aerosol composition variations: two size-driven factors that are related to new particle formation (NPF) and growth (F4 and F3), as well as two bulk factors driven by composition, not size (F2 and F1). The distribution of chemical species across these factors shows that different compounds are responsible for nucleation and growth of new particles. The smallest-diameter size factor (F4) contains ammonium sulfate and organics and typically peaks during the daytime. Newly formed particles, represented by F4, are mainly correlated with wind from the southwesterly-westerly and easterly sectors that transport sulfur oxides (SOx), ammonia (NH3), and organic precursors to Cabauw. As the particles grow from F4 to F3 and to bulk factors, nitrate and organics play an increasing role, and the particle loading diurnal cycle shifts from daytime to a nighttime maximum. Greater organics availability makes secondary organic aerosol (SOA) more influential in summertime aerosol growth, principally due to volatility differences produced by seasonal variation in photooxidation and temperature.</p

Inverse modelling of carbonyl sulfide: implementation, evaluation and implications for the global budget

Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model-SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol-1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000-2012. The addition of 432 Gg a-1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a-1, which is closer to 738 Gg a-1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget..</p

The Combined Impact of Canopy Stability and Soil NOx Exchange on Ozone Removal in a Temperate Deciduous Forest

Ingles

A GC-IRMS method for measuring sulfur isotope ratios of carbonyl sulfide from small air samples

A new system was developed for measuring sulfur isotopes δ 33S and δ 34S from atmospheric carbonyl sulfide (COS) on small air samples of several liters, using pre-concentration and gas chromatography – isotope ratio mass spectrometry (GC-IRMS). Measurements of COS isotopes provide a tool for quantifying the COS budget, which will help towards better understanding climate feedback mechanisms. For a 4 liter sample at ambient COS mixing ratio, ~500 parts per trillion (ppt), we obtain a reproducibility error of 2.1 ‰ for δ 33S and 0.4 ‰ for δ 34S. After applying corrections, the uncertainty for an individual ambient air sample measurement is 2.5 ‰ for δ 33S and 0.9 ‰ for δ 34S. The ability to measure small samples allows application to a global-scale sampling program with limited logistical effort. To illustrate the application of this newly developed system, we present a timeseries of ambient air measurements, during the fall and winter of 2020 and 2021 in Utrecht, the Netherlands. The observed background values were δ 33S = 1.0 ± 3.4 ‰ and δ 34S = 15.5 ± 0.8 ‰ (VCDT). The maximum observed COS mixing ratios was only 620 ppt. This, in combination with the relatively high δ 34S suggests that the Netherlands receives little COS-containing anthropogenic emissions. We observed a change in COS mixing ratio and δ 34S with different air mass origin, as modelled with HYSPLIT backward trajectory analyses. An increase of 40 ppt in mean COS mixing ratio was observed between fall and winter, which is consistent with the expected seasonal cycle in the Netherlands. Additionally, we present the results of samples from a highway tunnel to characterize vehicle COS emissions and isotopic composition. The vehicle emissions were small, with COS/CO 2 being 0.4 ppt/ppm; the isotopic signatures are depleted relatively to background atmospheric COS

Combined assimilation of NOAA surface and MIPAS satellite observations to constrain the global budget of carbonyl sulfide

Carbonyl sulfide (COS), a trace gas in our atmosphere that leads to the formation of aerosols in the stratosphere, is taken up by terrestrial ecosystems. Quantifying the biosphere uptake of (COS) could provide a useful quantity to estimate Gross Primary Productivity. Some COS sources and sinks still contain large uncertainties, and several top down estimates of the COS budget point to an underestimation of sources especially in the tropics. We extended the inverse model TM5-4DVAR to assimilate MIPAS satellite data, in addition to NOAA surface data as used in a previous study. To resolve possible discrepancies among the two observational datasets, a bias correction scheme was implemented. A set of inversions is presented that explores the influence of the different measurement instruments and the settings of the prior fluxes. To evaluate the performance of the inverse system, the HIAPER Pole-to-Pole Observations (HIPPO) aircraft observations and NOAA airborne profiles are used. All inversions reduce the (COS) biosphere uptake from a prior value of 1053 GgS a-1 to much smaller values, depending on the inversion settings. These large adjustments of the biosphere uptake often turn parts of the Amazonia into a (COS) source. Only inversions that exclusively use MIPAS observations, or strongly reduce the prior errors on the biosphere flux maintain the Amazonia as a COS sink. Assimilating both NOAA surface data and MIPAS data requires a small bias correction for MIPAS data, mostly at higher latitudes, to correct for inconsistencies in the observational data and/or transport model errors. Analysis of the error reduction and posterior correlation between land and ocean fluxes indicates that co-assimilation of NOAA surface observations and MIPAS data better constrains the (COS) budget than assimilation of one individual dataset alone. Our inversions with bias corrections reduce the global biosphere uptake to respectively 570 and 687 GgS a-1, depending on the prior biosphere error. Over the Amazonia, these inversions reduce the biosphere uptake from roughly 300 to 100 GgS a-1, indicating a strongly overestimated prior uptake over the Amazonia. Although a recent study also reported reduced (COS) uptake over the Amazonia, we emphasise that a careful construction of prior fluxes and their associated errors remains important. For instance, an inversion that gives large freedom to adjust the anthropogenic and ocean fluxes of CS2, an important (COS) precursor, also closes the budget satisfactorily with much smaller adjustments to the biosphere. Thus, a better characterisation of biosphere and ocean fluxes by observations is urgently needed, especially over the data-poor tropics

Global 3-D Simulations of the Triple Oxygen Isotope Signature Δ17O in Atmospheric CO2

The triple oxygen isotope signature Δ¹⁷O in atmospheric CO₂, also known as its “¹⁷O excess,” has been proposed as a tracer for gross primary production (the gross uptake of CO₂ by vegetation through photosynthesis). We present the first global 3-D model simulations for Δ¹⁷O in atmospheric CO₂ together with a detailed model description and sensitivity analyses. In our 3-D model framework we include the stratospheric source of Δ¹⁷O in CO₂ and the surface sinks from vegetation, soils, ocean, biomass burning, and fossil fuel combustion. The effect of oxidation of atmospheric CO on Δ¹⁷O in CO2 is also included in our model. We estimate that the global mean Δ¹⁷O (defined as Δ¹⁷O = ln( ¹⁷O + 1) − RL · ln( ¹⁸O + 1) with RL = 0.5229) of CO₂ in the lowest 500 m of the atmosphere is 39.6 per meg, which is ∼20 per meg lower than estimates from existing box models. We compare our model results with a measured stratospheric Δ¹⁷O in CO₂ profile from Sodankylä (Finland), which shows good agreement. In addition, we compare our model results with tropospheric measurements of Δ¹⁷O in CO₂ from Göttingen (Germany) and Taipei (Taiwan), which shows some agreement but we also find substantial discrepancies that are subsequently discussed. Finally, we show model results for Zotino (Russia), Mauna Loa (United States), Manaus (Brazil), and South Pole, which we propose as possible locations for future measurements of Δ¹⁷O in tropospheric CO₂ that can help to further increase our understanding of the global budget of Δ¹⁷O in atmospheric CO₂

Global Atmospheric δ13CH4 and CH4 Trends for 2000–2020 from the Atmospheric Transport Model TM5 Using CH4 from Carbon Tracker Europe–CH4 Inversions

This study investigates atmospheric δ13CH4 trends, as produced by a global atmospheric transport model using CH4 inversions from CarbonTracker-Europe CH4 for 2000–2020, and compares them to observations. The CH4 inversions include the grouping of the emissions both by δ13CH4 isotopic signatures and process type to investigate the effect, and to estimate the CH4 magnitudes and model CH4 and δ13CH4 trends. In addition to inversion results, simulations of the global atmospheric transport model were performed with modified emissions. The estimated global CH4 trends for oil and gas were found to increase more than coal compared to the priors from 2000–2006 to 2007–2020. Estimated trends for coal emissions at 30∘ N–60∘ N are less than 50% of those from priors. Estimated global CH4 rice emissions trends are opposite to priors, with the largest contribution from the EQ to 60∘ N. The results of this study indicate that optimizing wetland emissions separately produces better agreement with the observed δ13CH4 trend than optimizing all biogenic emissions simultaneously. This study recommends optimizing separately biogenic emissions with similar isotopic signature to wetland emissions. In addition, this study suggests that fossil-based emissions were overestimated by 9% after 2012 and biogenic emissions are underestimated by 8% in the inversion using EDGAR v6.0 as priors