Is the biosphere-atmosphere exchange of total reactive nitrogen above forest driven by the same factors as carbon dioxide? An analysis using artificial neural networks

Zöll, Undine; Moffat, Antje Maria; Wintjen, Pascal; Schrader, Frederik; Beudert, Burkhard; Brümmer, Christian

doi:10.1016/j.atmosenv.2019.02.042

Cited by 15 publications

(32 citation statements)

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“…As shown by Hurkuck et al (2014) N r concentrations at BOG were relatively high and showed a distinct diurnal cycle due to intensive livestock and crop production in the surrounding region which is in contrast to the situation at the remote FOR site. There were almost no nearby anthropogenic sources (Zöll et al, 2019) and hence much lower concentration (Beudert and Breit, 2010) and a weaker daily cycle were observed. This has an influence on the variability of (co)spectra and strengthens their susceptibility to noise.…”

Section: Noise Effects On Power Spectra and Cospectramentioning

confidence: 99%

“…Due to the measurement of the sum of individual N r compounds we can only roughly estimate the contribution of individual species to the flux and its high frequency loss. Hurkuck et al (2014) and Zöll et al (2016) Zöll et al (2019), NH 3 concentrations were relatively low at FOR site (Beudert and Breit, 2010). 33% of ΣN r were NH 3 and 32% were attributed to NO 2 .…”

Section: Noise Effects On Power Spectra and Cospectramentioning

confidence: 99%

“…However, these instruments typically have a low time resolution and require inferential modeling for estimating fluxes (e.g., Hurkuck et al, 2014). Recently, new measurement techniques for N r compounds were developed, such as quantum cascade lasers (QCL) using Tunable Infrared Laser Differential Absorption Spectroscopy (TILDAS) (Ferrara et al, 2012;Zöll et al, 2016;Moravek et al, in review, 2019) or the total reactive nitrogen converter (TRANC) (Marx et al, 2012;Ammann et al, 2012;Brümmer et al, 2013;Zöll et al, 2019) coupled to a fastresponse chemiluminescene detector (CLD) which have a certain robustness, a high sampling frequency and are sensitive enough to allow EC measurements of NH 3 or ΣN r .…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, concentrations of N r species such as NH 3 (1.3 ppb), NO (0.4-1.5 ppb), and NO 2 (1.9-4.4 ppb) were very low (Beudert and Breit, 2010). A detailed description of the forest site can be found in Zöll et al (2019). For the attenuation analysis data from June 2016 to end of June 2018 were selected.…”

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confidence: 99%

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Correcting high-frequency losses of reactive nitrogen flux measurements

Wintjen¹,

Ammann²,

Schrader³

et al. 2019

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Abstract. The eddy-covariance (EC) technique is nowadays widely used in experimental field studies to measure land surface-atmosphere exchange of a variety of trace gases. In recent years applying the EC technique to reactive nitrogen compounds has become more important since atmospheric nitrogen deposition influences the productivity and biodiversity of (semi-)natural ecosystems and its carbon dioxide (CO2) exchange. Fluxes which are calculated by EC have to be corrected for setup-specific effects like attenuation in the high-frequency range. However, common methods for correcting such flux losses are mainly optimized for inert greenhouse gases like CO2 and methane or water vapor. In this study, we applied a selection of correction methods to measurements of total reactive nitrogen (ΣNr) conducted in different ecosystems using the Total Reactive Atmospheric Nitrogen Converter (TRANC) coupled to a chemiluminescence dectector (CLD). Average flux losses calculated by methods using measured cospectra and ogives were about 26–38 % for a semi-natural peatland and about 16–22 % for a mixed forest. The investigation of the different methods showed that damping factors calculated with measured heat and gas flux cospectra using an empirical spectral transfer function were most reliable. Flux losses of ΣNr with this method were on the upper end of the median damping range, i.e. 38 % for the peatland site and 22 % for the forest site. Using modified Kaimal cospectra for damping estimation worked well for the forest site, but underestimates damping for the peatland site by about 12 %. Correction factors of methods based on power spectra or on site-specific and instrumental parameters were mostly less than 10 %. Power spectra of ΣNr were heavily affected likely by white noise and deviated substantially at lower frequencies from the temperature (power) spectrum. Our study suggests using an empirical method for estimating flux losses of ΣNr or any reactive nitrogen compound and locally measured cospectra.

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Section: Noise Effects On Power Spectra and Cospectramentioning

confidence: 99%

Section: Noise Effects On Power Spectra and Cospectramentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Correcting high-frequency losses of reactive nitrogen flux measurements

Wintjen¹,

Ammann²,

Schrader³

et al. 2019

Preprint

Self Cite

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“…can be used for flux calculation based on the eddy-covariance (EC) technique. The TRANC-CLD system has been shown to be suitable for EC measurements above a number of different ecosystems (see Ammann et al, 2012;Brümmer et al, 2013;Zöll et al, 2019;Wintjen et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Forest-atmosphere exchange of reactive nitrogen in a low polluted area – temporal dynamics and annual budgets

Wintjen

Schrader

Schaap

et al. 2020

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Abstract. Accurate modeling of nitrogen deposition is essential for identifying exceedances of critical loads and designing effective mitigation strategies. However, there are still uncertainties in modern deposition routines due to a limited availability of long-term flux measurements of reactive nitrogen compounds for model development and validation. In this study, we investigate the performance of dry deposition inferential models with regard to annual budgets and the exchange patterns of total reactive nitrogen (ΣNr) at a low-polluted mixed forest located in the Bavarian Forest National Park (NPBW), Germany. Flux measurements of ΣNr were carried out with a Total Reactive Atmospheric Nitrogen Converter (TRANC) coupled to a chemiluminescence dectector (CLD) for 2.5 years. Average ΣNr concentration was approximately 5.2 ppb. Denuder measurements with DELTA samplers and chemiluminescence measurements of nitrogen oxides (NOx) have shown that NOx has the highest contribution to ΣNr (~52%), followed by ammonia (NH3) (~ 22 %), ammonium (NH4+) (~ 14 %), nitrate NO3− (~ 7 %), and nitric acid (HNO3) (~ 6 %). We observed mostly deposition fluxes at the measurement site with median fluxes ranging from −15 ng N m−2 s−1 to −5 ng N m−2 s−1 (negative fluxes indicate deposition). In general, highest deposition was recorded from May to September. ΣNr deposition was enhanced by higher temperatures, lower relative humidity, high ΣNr concentration, and dry leaf surfaces. Our results suggest that dry conditions seem to favour nitrogen dry deposition at natural ecosystems. For determining annual dry deposition budgets we used the bidirectional inferential scheme DEPAC (DEPosition of Acidifying Compounds) with locally measured input parameters, called DEPAC-1D, as gap-filling strategy for TRANC measurements. In a second approach, the mean-diurnal-variation method (MDV) was applied to gaps of up to five days whereas DEPAC-1D was used for remaining gaps. We compared them to results from the chemical transport model LOTOS-EUROS (LOng Term OzoneSimulation – EURopean Operational Smog) v2.0 and from the canopy budget technique conducted at the measurement site. After 2.5 years, dry deposition based on TRANC measurements resulted in (11.1 ± 3.4) kg N ha−1 with DEPAC-1D as gap-filling method and (10.9 ± 3.8) kg N ha−1 with MDV and DEPAC-1D as gap-filling methods. Both values are close to dry deposition by DEPAC-1D (13.6 kg N ha−1) considering the uncertainties of measured fluxes and possible uncertainty sources of DEPAC-1D. The difference of DEPAC-1D to TRANC can be related to parameterizations of reactive gases or the missing exchange path with soil. 16.8 kg N ha−1 deposition were calculated by LOTOS-EUROS for considering land-use class weighting. We further showed that predicted NH3 concentrations, an input parameter of LOTOS-EUROS, were the main reason for the discrepancyin dry deposition budgets between the different methods. On average, annual TRANC dry deposition was 4.5 kg N ha−1 a−1 for both gap-filling approaches, DEPAC-1D showed 5.3 kg N ha−1 a−1, and LOTOS-EUROS modeled 5.2 kg N ha−1 a−1 to 6.9 kg N ha−1 a−1 depending on the weighting of land-use classes within the site's grid cell. 7.5 kg N ha−1 a−1 was estimated with the canopy budget technique for the period from 2016 to 2018 as upper estimate and 4.6 kg N ha−1 a−1 as lower estimate. Our findings provide a better understanding of exchange dynamics occurring at low-polluted, natural ecosystems and show opportunities for further development of deposition models.

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