Ammonia emissions in Europe, part I: Development of a dynamical ammonia emission inventory

Backes, A.; Aulinger, Armin; Bieser, Johannes; Matthias, Volker; Quante, Markus

doi:10.1016/j.atmosenv.2016.01.041

Cited by 77 publications

(52 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For housing operations, the daily factors are assumed to be dependent on the barn air temperature and ventilation rate, following Eq. (13): following Backes et al (2016). The daily factors for yarding and storage activities also follow Eq.…”

Section: Livestockmentioning

confidence: 99%

“…While this is again true for Spain, there are some European countries (e.g. Germany) in which the application of fertilizer is prohibited during certain periods (Backes et al, 2016). In this sense, it is expected that the emission approaches will be refined in future versions of HERMESv3_BU.…”

Section: Technical Implementationmentioning

confidence: 99%

“…spatially constant) and do not account for the dynamical component of the emission processes (e.g. volatilization of ammonia as a function of meteorological parameters; Backes et al, 2016). Moreover, existing global and regional emission inventories are reported following sector aggregations (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

HERMESv3, a stand-alone multiscale atmospheric emission modelling framework – Part 2: bottom-up module

Guevara¹,

Tena²,

Porquet³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. We describe the bottom-up module of the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), a python-based and multiscale modelling tool intended for the processing and computation of atmospheric emissions for air quality modelling. HERMESv3 is composed of two separate modules: the global_regional module and the bottom_up module. In a companion paper (Part 1, Guevara et al., 2019) we presented the global_regional module. The bottom_up module described in this contribution is an emission model that estimates anthropogenic emissions at high spatial (e.g. road link level) and temporal (hourly) resolution using state-of-the-art calculation methods that combine local activity and emission factors along with meteorological data. The model computes bottom-up emissions from point sources, road transport, residential and commercial combustion, other mobile sources and agricultural activities. The computed pollutants include main criteria pollutants (i.e. NOx, CO, NMVOC, SOx, NH3, PM10 and PM2.5) and greenhouse gases (i.e. CO2 and CH4, only related to combustion processes). Specific emission estimation methodologies are provided for each source, and are mostly based on (but not limited to) the calculation methodologies reported by the European EMEP/EEA air pollutant emission inventory guidebook. Meteorological-dependent functions are also included to take into account the dynamical component of the emission processes. The model also provides several functionalities for automatically manipulating and performing spatial operations on georeferenced objects (shapefiles and raster files). The model is designed so that it can be applicable to any European country/region where the required input data is available. As in the case of the global_regional module, emissions can be estimated on several user-defined grids, mapped to multiple chemical mechanisms and adapted to the input requirements of different atmospheric chemistry models (CMAQ, WRF-Chem and MONARCH) as well as a street-level dispersion model (R-LINE). Specific emission outputs generated by the model are presented and discussed to illustrate its capabilities.

show abstract

Section: Livestockmentioning

confidence: 99%

Section: Technical Implementationmentioning

confidence: 99%

See 1 more Smart Citation

HERMESv3, a stand-alone multiscale atmospheric emission modelling framework – Part 2: bottom-up module

Guevara¹,

Tena²,

Porquet³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Las emisiones de NH3 a la atmósfera y su deposición en el ambiente juegan un papel crucial en la acidificación y eutrofización de los ecosistemas y contribuye a las emisiones indirectas de óxido nitroso [35]. Los efectos adversos, como la eutrofización y acidificación de los ecosistemas [24], van a provocar la reducción de la biodiversidad [12], constituyendo un importante precursor de la formación de partículas finas en la atmósfera [4,5,19]. En las proximidades de las granjas de cerdos se observaron concentraciones ambientales importantes [15,22,44].…”

Section: Introductionunclassified

Tecnología de la producción animal / Acuicultura Evolución de la concentración de NH3 en función de la temperatura de consigna en alojamientos porcinos de transición

Rodríguez¹,

Besteiro²,

Arango³

et al. 2019

Congreso Ibérico De Agroingeniería

View full text Add to dashboard Cite

“…Furthermore, livestock farming and fertilizer application account for 85% of ammonium emissions over the SCB. A host of evidence shows that agricultural sources contributed a major portion of NH 3 emissions, approximately 80-90% of total anthropogenic emission [65]. Certain regions exhibit different seasonal characteristics, such as Guangzhou and the SCB, where autumn concentrations are higher than summer concentrations.…”

Section: Seasonal Variations In Pm 25 Chemical Componentsmentioning

confidence: 99%

Estimation of Satellite-Based SO42− and NH4+ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model

Chen

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

Abstract:Epidemiologic and health impact studies have examined the chemical composition of ambient PM 2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM 2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM 2.5 data with a spatial resolution of 0.1 × 0.1 • , we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of −35.9%, NME of 48.2%, ARB_50% of 53.68% for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO −0.61%; NH 4 + : −0.21%), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO 2 ) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population's exposure to certain chemical components.

show abstract

Ammonia emissions in Europe, part I: Development of a dynamical ammonia emission inventory

Cited by 77 publications

References 38 publications

HERMESv3, a stand-alone multiscale atmospheric emission modelling framework – Part 2: bottom-up module

HERMESv3, a stand-alone multiscale atmospheric emission modelling framework – Part 2: bottom-up module

Tecnología de la producción animal / Acuicultura Evolución de la concentración de NH3 en función de la temperatura de consigna en alojamientos porcinos de transición

Estimation of Satellite-Based SO42− and NH4+ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model

Contact Info

Product

Resources

About