High temporal resolution modelling of environmentally-dependent seabird ammonia emissions: Description and testing of the GUANO model

Riddick, Stuart N.; Blackall, T. D.; Dragosits, Ulrike; Tang, Y. S.; Móring, Andrea; Daunt, Francis; Wanless, Sarah; Hamer, Keith C.; Sutton, Mark A.

doi:10.1016/j.atmosenv.2017.04.020

Cited by 13 publications

(8 citation statements)

References 35 publications

(10 reference statements)

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“…We use an exponential term as the climate-adjustment factor to account for T, W, and P (Experimental Procedures) following previous studies. 12,43 The enhanced model (i.e., RFM C ) explains 95% of the V NH3,AG variance, significantly improved from the previous version. The model predictions resemble the gridded V NH3,AG values simulated by FEST-C_EPIC-CMAQ_BIDI (Figures S9A and S9B).…”

Section: Introductionmentioning

confidence: 91%

“…In most studies as well as in RFM C , it is assumed that the longterm T dependency of V NH3,AG over agricultural land follows a similar function as that of natural circumstances, e.g., seabird colonies, where ln(V NH3 ) is a linear function of 1/T as Dln(V NH3 ) = a$D(1/T), where the values of a are always negative and differ by LC type (Experimental Procedures). 12,43 The sensitivity of V NH3 to T (S V,T , denotes the percentage change in V NH3 to the absolute change in T) derived from the V NH3~T function is inversely proportional to T 2 (S V,T = Àa/T 2 ), indicating that V NH3 becomes less sensitive to T at higher T levels. Our RFM C shows an a value of À8,690 K for unirrigated crop, equivalent to an S V,T of 10.2% K À1 at 18 C and a slightly lower S V,T (9.8% K À1 ) at 25 C. The S V,T directly calculated from FEST-C_EPIC-CMAQ_BIDI via a yearby-year comparison shows a very similar S V,T (10.2% K À1 ) at 18 C but a much lower S V,T (4.7% K À1 ) at 25 C. The difference between FEST-C_EPIC-CMAQ_BIDI-modeled and RFM C -reproduced S V,T suggests that the V NH3,AG in RFM C is overly sensitive to T changes at higher T levels (Figure 2).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Intense Warming Will Significantly Increase Cropland Ammonia Volatilization Threatening Food Security and Ecosystem Health

Shen

Chen

et al. 2020

One Earth

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Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Intense Warming Will Significantly Increase Cropland Ammonia Volatilization Threatening Food Security and Ecosystem Health

Shen

Chen

et al. 2020

One Earth

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“…It is, however, unclear why NH 3 emissions are larger at Lake Natron than at other soda lakes with similar regularly exposed mudflats. Other known natural point sources include seal and seabird colonies and volcanoes [25][26][27] . Bird colonies are found in coastal areas and especially at high latitudes.…”

mentioning

confidence: 99%

Industrial and agricultural ammonia point sources exposed

Damme

Clarisse

Hadji‐Lazaro

et al. 2018

Nature

347

312

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Through its important role in the formation of particulate matter, atmospheric ammonia affects air quality and has implications for human health and life expectancy 1,2. Excess ammonia in the environment also contributes to the acidification and eutrophication of ecosystems 3-5 and to climate change 6. Anthropogenic emissions dominate natural ones and mostly originate from agricultural, domestic and industrial activities 7. However, the total ammonia budget and the attribution of emissions to specific sources remain highly uncertain across different spatial scales 7-9. Here we identify, categorize and quantify the world's ammonia emission hotspots using a high-resolution map of atmospheric ammonia obtained from almost a decade of daily IASI satellite observations. We report 248 hotspots with diameters smaller than 50 kilometres, which we associate with either a single point source or a cluster of agricultural and industrial point sources-with the exception of one hotspot, which can be traced back to a natural source. The state-of-the-art EDGAR emission inventory 10 mostly agrees with satellitederived emission fluxes within a factor of three for larger regions. However, it does not adequately represent the majority of point sources that we identified and underestimates the emissions of two-thirds of them by at least one order of magnitude. Industrial emitters in particular are often found to be displaced or missing. Our results suggest that it is necessary to completely revisit the emission inventories of anthropogenic ammonia sources and to account for the rapid evolution of such sources over time. This will lead to better health and environmental impact assessments of atmospheric ammonia and the implementation of suitable nitrogen management strategies. Considerable effort goes into establishing spatially and temporally resolved ammonia (NH 3) bottom-up emission inventories, as these are critical drivers of models that are used to assess NH 3 distributions and impacts on the environment. Bottom-up inventories are built from activity data coupled with estimated emission factors. The correctness of these input data is their Achilles' heel, as activity data can be absent or outdated and estimated emission factors are based on specific case studies and may not be representative of either local or global conditions 11,12. When they are available, global measured atmospheric distributions of trace gas concentrations allow us to retrieve source emissions. In the past few years, satellite sounders have offered (bi) daily global NH 3 measurements 13-17 , which have a huge potential to improve our knowledge of the NH 3 emission budget 18. The first global distributions 13 and inverse modelling efforts 19 have confirmed the correctness of the location of the large source regions in the inventories, but have also revealed likely underestimates in the magnitude of their emissions, especially in the Northern Hemisphere. A regional study 20 has highlighted the advantage of averaging data to reveal smaller, localized NH 3 point...

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“…Pinder et al (2004) developed a process-based model for simulating NH 3 emissions from dairy cows, and the modelled NH 3 volatilization fraction from grazing, manure spreading and storage was shown to be reasonable compared to independent experimental data. Previous process-modelling efforts for bird sources have focused on native seabird populations (Riddick et al, 2016(Riddick et al, , 2018, using these as a natural laboratory to study the effect of global climate differences on NH 3 emissions, supported by a programme of measurements through different climates (Blackall et al, 2007;Riddick et al 2012). Process-based models consider the effects of meteorological variation on the formation of NH 3 from an N r source, allowing the calculation of NH 3 emissions that vary temporally and spatially.…”

Section: Introductionmentioning

confidence: 99%

A climate-dependent global model of ammonia emissions from chicken farming

et al. 2021

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Abstract. Ammonia (NH3) has significant impacts on the environment, which can influence climate and air quality and cause acidification and eutrophication in terrestrial and aquatic ecosystems. Agricultural activities are the main sources of NH3 emissions globally. Emissions of NH3 from chicken farming are highly dependent on climate, affecting their environmental footprint and impact. In order to investigate the effects of meteorological factors and to quantify how climate change affects these emissions, a process-based model, AMmonia–CLIMate–Poultry (AMCLIM–Poultry), has been developed to simulate and predict temporal variations in NH3 emissions from poultry excretion, here focusing on chicken farms and manure spreading. The model simulates the decomposition of uric acid to form total ammoniacal nitrogen, which then partitions into gaseous NH3 that is released to the atmosphere at an hourly to daily resolution. Ammonia emissions are simulated by calculating nitrogen and moisture budgets within poultry excretion, including a dependence on environmental variables. By applying the model with global data for livestock, agricultural practice and meteorology, we calculate NH3 emissions from chicken farming on a global scale (0.5∘ resolution). Based on 2010 data, the AMCLIM–Poultry model estimates NH3 emissions from global chicken farming of 5.5 ± 1.2 Tg N yr−1, about 13 % of the agriculture-derived NH3 emissions. Taking account of partial control of the ambient environment for housed chicken (layers and broilers), the fraction of excreted nitrogen emitted as NH3 is found to be up to 3 times larger in humid tropical locations than in cold or dry locations. For spreading of manure to land, rain becomes a critical driver affecting emissions in addition to temperature, with the emission fraction being up to 5 times larger in the semi-dry tropics than in cold, wet climates. The results highlight the importance of incorporating climate effects into global NH3 emissions inventories for agricultural sources. The model shows increased emissions under warm and wet conditions, indicating that climate change will tend to increase NH3 emissions over the coming century.

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High temporal resolution modelling of environmentally-dependent seabird ammonia emissions: Description and testing of the GUANO model

Cited by 13 publications

References 35 publications

Intense Warming Will Significantly Increase Cropland Ammonia Volatilization Threatening Food Security and Ecosystem Health

Intense Warming Will Significantly Increase Cropland Ammonia Volatilization Threatening Food Security and Ecosystem Health

Industrial and agricultural ammonia point sources exposed

A climate-dependent global model of ammonia emissions from chicken farming

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