Reactive nitrogen emissions from crop and livestock farming in India

Aneja, Viney P.; Schlesinger, William H.; Erisman, J. W.; Behera, S. N.; Sharma, Mukesh; Battye, William

doi:10.1016/j.atmosenv.2011.11.026

Cited by 76 publications

(53 citation statements)

References 57 publications

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“…about one-third of the EDGAR (2011) global emission estimate of 40.6 Tg NH 3 -N yr −1 , but subject to huge uncertainty. Aneja et al (2012) estimate that NH 3 emissions from livestock could be a factor of 2-3 higher than their best estimate, while emissions from fertilizer application could be up to 40 % lower than they estimated.…”

Section: Global Scalementioning

confidence: 84%

“…There is a major lack of knowledge on agricultural management practices in many parts of the world and on the effect of the many climates and soils of the world on emission processes, especially the interplay of temperature and moisture. With 37 % of the world's population between them, China and India's collective NH 3 emissions account for around 13.5 Tg NH 3 -N yr −1 (Huang et al, 2012;Aneja et al, 2012), i.e. about one-third of the EDGAR (2011) global emission estimate of 40.6 Tg NH 3 -N yr −1 , but subject to huge uncertainty.…”

Section: Global Scalementioning

confidence: 99%

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Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

et al. 2013

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Atmospheric ammonia (NH₃) dominates global emissions of total reactive nitrogen (N_r), while emissions from agricultural production systems contribute about two-thirds of global NH₃ emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH₃ emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH₄⁺) to all surfaces. However, the land/atmosphere exchange of gaseous NH₃ is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH₃ emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH₃ emission potentials defined at the substrate and leaf levels by different [NH₄⁺] / [H⁺] ratios (Γ). Surface/atmosphere exchange models for NH₃ are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH₃ and NH₄⁺. Models of soil/vegetation/atmosphere NH₃ exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations

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Section: Global Scalementioning

confidence: 84%

Section: Global Scalementioning

confidence: 99%

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

et al. 2013

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“…We also performed a region‐based analysis for India, and China using the NH 3 _STAT model. The NH 3 _STAT model estimate for India (2.2 Tg N yr −1 ) shows lower NH 3 emissions than EDGAR (5.3 Tg N yr −1 ) and Aneja et al () (3.9 Tg N yr −1 ), respectively. For China, the model estimates NH 3 emissions from fertilizer (1.7 Tg N yr −1 ) that are lower than other data sets (e.g., Huang et al () (3.2 Tg N yr −1 ), Cui et al () (10 Tg N yr −1 ), and Gu et al () (7.7 Tg N yr −1 )).…”

Section: Resultsmentioning

confidence: 61%

Characterization of the Global Sources of Atmospheric Ammonia from Agricultural Soils

Aneja

Schlesinger

et al. 2020

JGR Atmospheres

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Global ammonia (NH 3 ) emissions to the atmosphere are projected to increase in the coming years with the increased use of synthetic nitrogen fertilizers and cultivation of nitrogen-fixing crops. A statistical model (NH 3 _STAT) is developed for characterizing atmospheric NH 3 emissions from agricultural soils and compared to the performance of other global and regional NH 3 models (e.g., Emission Database for Global Atmospheric Research, Magnitude and Seasonality of Agricultural Emissions, MIX, and U.S. Environmental Protection Agency). The statistical model was developed from a multiple linear regression between NH 3 emission and the physicochemical variables. The model was evaluated for 2012 NH 3 emissions. The results indicate that, in comparison to other data sets, the model provides a lower global NH 3 estimate by 58%, (NH 3 _STAT: 13.9 Tg N yr −1 ; Emission Database for Global Atmospheric Research: 33.0 Tg N yr −1 ). We also performed a region-based analysis (United States, India, and China) using the NH 3 _STAT model. For the United States, our model produces an estimate that is a~1.4 times higher in comparison to the Environmental Protection Agency. Meanwhile, the NH 3 _STAT estimate for India shows NH 3 emissions between 0.8 and 1.4 times lower when compared to other data sets. A lower estimate is also seen for China, where the model estimates NH 3 emissions 0.4 to 5 times lower than other data sets. The difference in the global estimates is attributed to the lower estimates in major agricultural countries like China and India. The statistical model captures the spatial distribution of global NH 3 emissions by utilizing a simplified approach compared to other readily available data sets. Moreover, the NH 3 _STAT model provides an opportunity to predict future NH 3 emissions in a changing world. − ), and nitrous oxide (N 2 O); and organic nitrogen such as urea, amino acids, and proteins. Many of these are biologically active, chemically reactive, and radiatively active in the Earth's atmosphere and biosphere, in contrast to nonreactive nitrogen gas (N 2 ).

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“…N 2 O emissions increase with the use of nitrogen fertilizers [29][30], from manure and urine excreta applied and aerobic and anaerobic degradation of livestock waste in the lagoons and dry manure piles [31]. According to [32], the urea contributed the highest proportion of N 2 O emissions (74.8%) among the fertilizers. The high N 2 O emission rates generally corresponding with soil conditions are necessary to denitrification, and nitrification is often an essential prerequisite for the conversion of N fertilizer inputs into soil NO 3 - [33].…”

Section: Introductionmentioning

confidence: 99%

Nitrous Oxide Release from Poultry and Pig Housing

Brouček¹

2018

Pol. J. Environ. Stud.

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The article investigates the scientific literature regarding N 2 O emissions according to housing and manure management in poultry and pig buildings. The majority of the N 2 O is emitted from manure storages and housing space, with small amounts emitted from the surface of passages. Many factors must be considered in successful emission evaluation, including season of the year, amount and depth of the bedding, animal density, type and floor space, feeding and watering practices, ventilation, temperature, and relative humidity. The liquid manure from poultry housing systems produces greater emissions of N 2 O than natural and force-dried manure. The influencing factors appeared to be manure removal frequency and the dry matter content of the manure. There are more housing types in pig barns, which differ in bedding, floor, and manure deposition. The highest N 2 O emissions were found in the sawdust bedding, and N 2 O production in slatted floor housing is lowest. This paper reports on technical options for mitigating emissions from poultry and swine contributions. The actual rate of N 2 O emission is highly dependent on the management strategies implemented on a farm. Consequently, improvements in management practices will affect future N 2 O emissions. Finally, emission factors are listed in a table.

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Reactive nitrogen emissions from crop and livestock farming in India

Abstract: All rights reserved. No part of this publication may be reproduced, utilised in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system without permisssion in writing from the publishers.

Cited by 76 publications

References 57 publications

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

Characterization of the Global Sources of Atmospheric Ammonia from Agricultural Soils

Nitrous Oxide Release from Poultry and Pig Housing

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