Quantifying the dry deposition of reactive nitrogen and sulfur containing species in remote areas using a surrogate surface analysis approach

2004 ◽  
Vol 38 (17) ◽  
pp. 2687-2697 ◽  
Author(s):  
Heather A Raymond ◽  
Seung-Muk Yi ◽  
Nadjoua Moumen ◽  
YoungJi Han ◽  
Thomas M Holsen
2020 ◽  
Vol 223 ◽  
pp. 117196 ◽  
Author(s):  
Justin G. Coughlin ◽  
Emily M. Elliott ◽  
Lucy A. Rose ◽  
Natalie J. Pekney ◽  
Matthew Reeder

2020 ◽  
Vol 20 (8) ◽  
pp. 4933-4949 ◽  
Author(s):  
Genki Katata ◽  
Kazuhide Matsuda ◽  
Atsuyuki Sorimachi ◽  
Mizuo Kajino ◽  
Kentaro Takagi

Abstract. Dry deposition has an impact on nitrogen status in forest environments. However, the mechanism for the high dry-deposition rates of fine nitrate particles (NO3-) observed in forests remains unknown and is thus a potential source of error in chemical transport models (CTMs). Here, we modified and applied a multilayer land surface model coupled with dry-deposition and aerosol dynamic processes for a temperate mixed forest in Japan. This represents the first application of such a model to ammonium nitrate (NH4NO3) gas–particle conversion (gpc) and the aerosol water uptake of reactive nitrogen compounds. Thermodynamics, kinetics, and dry deposition for mixed inorganic particles are modeled by a triple-moment modal method. Data for inorganic mass and size-resolved total number concentrations measured by a filter pack and electrical low-pressure impactor in autumn were used for model inputs and subsequent numerical analysis. The model successfully reproduces turbulent fluxes observed above the canopy and vertical micrometeorological profiles noted in our previous studies. The sensitivity tests with and without gpc demonstrated clear changes in the inorganic mass and size-resolved total number concentrations within the canopy. The results also revealed that within-canopy evaporation of NH4NO3 under dry conditions significantly enhances the deposition flux of fine-NO3- and fine-NH4+ particles, while reducing the deposition flux of nitric acid gas (HNO3). As a result of the evaporation of particulate NH4NO3, the calculated daytime mass flux of fine NO3- over the canopy was 15 times higher in the scenario of “gpc” than in the scenario of “no gpc”. This increase caused high contributions from particle deposition flux (NO3- and NH4+) to total nitrogen flux over the forest ecosystem (∼39 %), although the contribution of NH3 was still considerable. A dry-deposition scheme coupled with aerosol dynamics may be required to improve the predictive accuracy of chemical transport models for the surface concentration of inorganic reactive nitrogen.


2020 ◽  
Author(s):  
Pascal Wintjen ◽  
Frederik Schrader ◽  
Martijn Schaap ◽  
Burkhard Beudert ◽  
Christian Brümmer

<p>Reactive nitrogen (N<sub>r</sub>) compounds comprise essential nutrients for plants. However, a large supply of nitrogen by fertilization through atmospheric deposition may be harmful for ecosystems such as peatlands and may lead to a loss of biodiversity, soil acidification and eutrophication. In addition, nitrogen compounds may cause adverse human health impacts. Large parts of N<sub>r</sub> emissions originate from anthropogenic activities.  Emission hotspots of ΣN<sub>r</sub>, i.e. the sum of all N<sub>r</sub> compounds, are related to crop production and livestock farming (mainly through ammonia, NH<sub>3</sub>) and fossil fuel combustion by transport and industry (mainly through nitrogen oxides, NO<sub>2 </sub>and NO). Such additional amount of N<sub>r</sub> will enhance its biosphere-atmosphere exchange, affect plant health and can influence its photosynthetic capacity. Therefore, it is necessary to thoroughly estimate the nitrogen exchange between biosphere and atmosphere.</p><p>For measuring the nitrogen mixing ratios a converter for reactive nitrogen (TRANC: Total Reactive Atmospheric Nitrogen Converter) was used. The TRANC converts all reactive nitrogen compounds, except for nitrous oxide (N<sub>2</sub>O), to nitric oxide (NO) and is coupled to a fast-response chemiluminescence detector (CLD). Due to a low detection limit and a response time of about 0.3s the TRANC-CLD system can be used for flux calculation based on the eddy covariance (EC) technique. Flux losses, which are related to the experimental setup, different response characteristics and the general high reactivity of most N gases and aerosols, occur in the high frequency range. We estimated damping factors of approximately 20% with an empirical cospectral approach.</p><p>For getting a reliable prediction of ΣN<sub>r</sub> fluxes through deposition models, long-term flux measurements offer the possibility to verify the nitrogen uptake capacity and to investigate exchange characteristics of ΣN<sub>r </sub>in different ecosystems.</p><p>In this study, we compare modelled dry deposition fluxes using the deposition module DEPAC (DEPosition of Acidifying Compounds) within the chemical transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) against ΣN<sub>r</sub> flux measurements of the TRANC-CLD for a remote mixed forest site with hardly any local anthropogenic emission sources. This procedure allows to determine the background load and the natural exchange characteristics of nitrogen under low atmospheric concentrations. Therefore, the broad-scale dry deposition predicted directly by LOTOS-EUROS was compared to site-specific modelling results obtained using measured meteorological input data as well as the directly measured ΣN<sub>r</sub> fluxes. In addition, the influence of land-use weighting in LOTOS-EUROS was examined. We further compare our results to ΣN<sub>r</sub> deposition estimates obtained with canopy budget techniques. Measured ΣN<sub>r</sub> dry deposition at the site was 4.5 kg N ha<sup>-</sup><sup>1</sup> yr<sup>-</sup><sup>1</sup>, in close agreement with modelled estimates using DEPAC with measured drivers (5.2 kg N ha<sup>-</sup><sup>1</sup> yr<sup>-</sup><sup>1</sup>) and as integrated in the chemical transport model LOTOS-EUROS (5.2 kg N ha<sup>-</sup><sup>1</sup> yr<sup>-</sup><sup>1</sup> to 6.9 kg N ha<sup>-</sup><sup>1</sup> yr<sup>-</sup><sup>1</sup> depending on the weighting of land-use classes).</p><p>Our study is the first one presenting 2.5 years flux measurements of ΣN<sub>r</sub> above a remote mixed forest. Further verifications of long-term flux measurements against deposition models are useful to improve them and result in better understanding of exchange processes of ΣN<sub>r</sub>.</p>


1995 ◽  
Vol 29 (21) ◽  
pp. 3209-3231 ◽  
Author(s):  
G. Kramm ◽  
R. Dlugi ◽  
G.J. Dollard ◽  
T. Foken ◽  
N. Mölders ◽  
...  

2011 ◽  
Vol 11 (6) ◽  
pp. 2703-2728 ◽  
Author(s):  
C. R. Flechard ◽  
E. Nemitz ◽  
R. I. Smith ◽  
D. Fowler ◽  
A. T. Vermeulen ◽  
...  

Abstract. Inferential models have long been used to determine pollutant dry deposition to ecosystems from measurements of air concentrations and as part of national and regional atmospheric chemistry and transport models, and yet models still suffer very large uncertainties. An inferential network of 55 sites throughout Europe for atmospheric reactive nitrogen (Nr) was established in 2007, providing ambient concentrations of gaseous NH3, NO2, HNO3 and HONO and aerosol NH4+ and NO3− as part of the NitroEurope Integrated Project. Network results providing modelled inorganic Nr dry deposition to the 55 monitoring sites are presented, using four existing dry deposition routines, revealing inter-model differences and providing ensemble average deposition estimates. Dry deposition is generally largest over forests in regions with large ambient NH3 concentrations, exceeding 30–40 kg N ha−1 yr−1 over parts of the Netherlands and Belgium, while some remote forests in Scandinavia receive less than 2 kg N ha−1 yr−1. Turbulent Nr deposition to short vegetation ecosystems is generally smaller than to forests due to reduced turbulent exchange, but also because NH3 inputs to fertilised, agricultural systems are limited by the presence of a substantial NH3 source in the vegetation, leading to periods of emission as well as deposition. Differences between models reach a factor 2–3 and are often greater than differences between monitoring sites. For soluble Nr gases such as NH3 and HNO3, the non-stomatal pathways are responsible for most of the annual uptake over many surfaces, especially the non-agricultural land uses, but parameterisations of the sink strength vary considerably among models. For aerosol NH4+ and NO3− discrepancies between theoretical models and field flux measurements lead to much uncertainty in dry deposition rates for fine particles (0.1–0.5 μm). The validation of inferential models at the ecosystem scale is best achieved by comparison with direct long-term micrometeorological Nr flux measurements, but too few such datasets are available, especially for HNO3 and aerosol NH4+ and NO3−.


2020 ◽  
Author(s):  
Athanasios Nenes ◽  
Maria Kanakidou ◽  
Spyros Pandis ◽  
Armistead Russell ◽  
Shaojie Song ◽  
...  

<p>Nitrogen oxides (NOx) and ammonia (NH<sub>3</sub>) from anthropogenic and biogenic emissions are central contributors to particulate matter (PM) concentrations worldwide. Ecosystem productivity can also be strongly modulated by the atmospheric deposition of this inorganic "reactive nitrogen" nutrient. The response of PM and nitrogen deposition to changes in the emissions of both compounds is typically studied on a case-by-case basis, owing in part to the complex thermodynamic interactions of these aerosol precursors with other PM constituents. In the absence of rain, much of the complexity of nitrogen deposition is driven by the large difference in dry deposition velocity when a nitrogen-containing molecule is in the gas or condensed phase.</p><p>Here we present a simple but thermodynamically consistent approach that expresses the chemical domains of sensitivity of aerosol particulate matter to NH<sub>3</sub> and HNO<sub>3</sub> availability in terms of aerosol pH and liquid water content. From our analysis, four policy-relevant regimes emerge in terms of sensitivity: i) NH<sub>3</sub>-sensitive, ii) HNO<sub>3</sub>-sensitive, iii) combined NH<sub>3</sub> and HNO<sub>3</sub> sensitive, and, iv) a domain where neither NH<sub>3</sub> and HNO<sub>3</sub> are important for PM levels (but only nonvolatile precursors such as NVCs and sulfate). When this framework is applied to ambient measurements or predictions of PM and gaseous precursors, the “chemical regime” of PM sensitivity to NH3 and HNO3 availability is directly determined. </p><p>The same framework is then extended to consider the impact of gas-to-particle partitioning, on the deposition velocity of NH<sub>3</sub> and HNO<sub>3</sub> individually, and combined affects the dry deposition of inorganic reactive nitrogen. Four regimes of deposition velocity emerge: i) HNO<sub>3</sub>-fast, NH<sub>3</sub>-slow, ii) HNO<sub>3</sub>-slow, NH<sub>3</sub>-fast, iii) HNO<sub>3</sub>-fast, NH<sub>3</sub>-fast, and, iv) HNO<sub>3</sub>-slow, NH<sub>3</sub>-slow. Conditions that favor strong partitioning of species to the aerosol phase strongly delay the deposition of reactive nitrogen species and promotes their accumulation in the boundary layer and potential for long-range transport. </p><p>The use of these regimes allows novel insights and is an important tool to evaluate chemical transport models. Most notably, we find that nitric acid displays considerable variability of dry deposition flux, with maximum deposition rates found in the Eastern US (close to gas-deposition rates) and minimum rates for North Europe and China. Strong reductions in deposition velocity lead to considerable accumulation of nitrate aerosol in the boundary layer –up to 10-fold increases in PM2.5 nitrate aerosol, eventually being an important contributor to high PM2.5 levels observed during haze episodes. With this new understanding, aerosol pH and associated liquid water content can be understood as control parameters that drive PM formation and dry deposition flux and arguably can catalyze the accumulation of aerosol precursors that cause intense haze events throughout the globe.</p>


2019 ◽  
Author(s):  
Mariana Souza ◽  
Felipe Pacheco ◽  
Maria Cristina Forti ◽  
Jalusa Aparecida Palandi ◽  
Joao Carvalho ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document