scholarly journals Direct nitrous oxide emissions in Mediterranean climate cropping systems: Emission factors based on a meta-analysis of available measurement data

2017 ◽  
Vol 238 ◽  
pp. 25-35 ◽  
Author(s):  
Maria L. Cayuela ◽  
Eduardo Aguilera ◽  
Alberto Sanz-Cobena ◽  
Dean C. Adams ◽  
Diego Abalos ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Mediterranean Climate ◽  
Cropping Systems ◽  
Meta Analysis ◽  
Measurement Data ◽  
Emission Factors ◽  
Nitrous Oxide Emissions

Yield-scaled nitrous oxide emissions from nitrogen-fertilized croplands in China: A meta-analysis of contrasting mitigation scenarios

Pedosphere ◽  
2021 ◽  
Vol 31 (2) ◽  
pp. 231-242
Author(s):  
Garba ALIYU ◽  
Jiafa LUO ◽  
Hong J. DI ◽  
Deyan LIU ◽  
Junji YUAN ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Meta Analysis ◽  
Nitrous Oxide Emissions ◽  
Mitigation Scenarios

scholarly journals Crop Yield and Nitrous Oxide Emissions following Swine Manure Application: A Meta‐Analysis

ael ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 190024 ◽  
Author(s):  
Weiquan Luo ◽  
Peter L. O'Brien ◽  
Jerry L. Hatfield
Keyword(s):  
Nitrous Oxide ◽  
Crop Yield ◽  
Meta Analysis ◽  
Swine Manure ◽  
Nitrous Oxide Emissions ◽  
Manure Application

Soil nitrous oxide emissions as affected by long-term tillage, cropping systems and nitrogen fertilization in Southern Brazil

2015 ◽  
Vol 146 ◽  
pp. 213-222 ◽  
Author(s):  
Cimélio Bayer ◽  
Juliana Gomes ◽  
Josiléia Accordi Zanatta ◽  
Frederico Costa Beber Vieira ◽  
Marisa de Cássia Piccolo ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Nitrogen Fertilization ◽  
Cropping Systems ◽  
Nitrous Oxide Emissions ◽  
Southern Brazil

Nitrous oxide emissions from fertilised UK arable soils: Fluxes, emission factors and mitigation

2015 ◽  
Vol 212 ◽  
pp. 134-147 ◽  
Author(s):  
M.J. Bell ◽  
N. Hinton ◽  
J.M. Cloy ◽  
C.F.E. Topp ◽  
R.M. Rees ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Emission Factors ◽  
Nitrous Oxide Emissions ◽  
Arable Soils

scholarly journals Opportunities for mitigating nitrous oxide emissions in subtropical cereal and fiber cropping systems: A simulation study

2016 ◽  
Vol 218 ◽  
pp. 11-27 ◽  
Author(s):  
Henrike Mielenz ◽  
Peter J. Thorburn ◽  
Clemens Scheer ◽  
Massimiliano De Antoni Migliorati ◽  
Peter R. Grace ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Simulation Study ◽  
Cropping Systems ◽  
Nitrous Oxide Emissions

Nitrous oxide emissions from contrasting organic cropping systems

2009 ◽  
Vol 6 (24) ◽  
pp. 242012
Author(s):  
Ngonidzashe Chirinda ◽  
J E Olesen ◽  
S O Petersen ◽  
J R Porter
Keyword(s):  
Nitrous Oxide ◽  
Cropping Systems ◽  
Nitrous Oxide Emissions

scholarly journals Emission factors for estimating fertiliser-induced nitrous oxide emissions from clay soils in Australia’s irrigated cotton industry

Soil Research ◽  
2016 ◽  
Vol 54 (5) ◽  
pp. 598 ◽  
Author(s):  
Peter Grace ◽  
Iurii Shcherbak ◽  
Ben Macdonald ◽  
Clemens Scheer ◽  
David Rowlings
Keyword(s):  
Nitrous Oxide ◽  
Meta Analysis ◽  
Exponential Model ◽  
N2o Emission ◽  
Nitrous Oxide Emissions ◽  
N2o Emissions ◽  
Tier 2 ◽  
Cotton Industry ◽  
Greenhouse Gas Inventories ◽  
N Rates

As a significant user of nitrogen (N) fertilisers, the Australian cotton industry is a major source of soil-derived nitrous oxide (N2O) emissions. A country-specific (Tier 2) fertiliser-induced emission factor (EF) can be used in national greenhouse gas inventories or in the development of N2O emissions offset methodologies provided the EFs are evidence based. A meta-analysis was performed using eight individual N2O emission studies from Australian cotton studies to estimate EFs. Annual N2O emissions from cotton grown on Vertosols ranged from 0.59kgNha–1 in a 0N control to 1.94kgNha–1 in a treatment receiving 270kgNha–1. Seasonal N2O estimates ranged from 0.51kgNha–1 in a 0N control to 10.64kgNha–1 in response to the addition of 320kgNha–1. A two-component (linear+exponential) statistical model, namely EF (%)=0.29+0.007(e0.037N – 1)/N, capped at 300kgNha–1 describes the N2O emissions from lower N rates better than an exponential model and aligns with an EF of 0.55% using a traditional linear regression model.

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