Synthesis and Review: Advancing agricultural greenhouse gas quantification

Reducing emissions of agricultural greenhouse gases (GHGs), such as methane and nitrous oxide, and sequestering carbon in the soil or in living biomass can help reduce the impact of agriculture on climate change while improving productivity and reducing resource use. There is an increasing demand for improved, low cost quantification of GHGs in agriculture, whether for national reporting to the United Nations Framework Convention on Climate Change (UNFCCC), underpinning and stimulating improved practices, establishing crediting mechanisms, or supporting green products. This ERL focus issue highlights GHG quantification to call attention to our existing knowledge and opportunities for further progress. In this article we synthesize the findings of 21 papers on the current state of global capability for agricultural GHG quantification and visions for its improvement. We conclude that strategic investment in quantification can lead to significant global improvement in agricultural GHG estimation in the near term

Synthesis and Review: Advancing agricultural greenhouse gas quantification

Reducing emissions of agricultural greenhouse gases (GHGs), such as methane and nitrous oxide, and sequestering carbon in the soil or in living biomass can help reduce the impact of agriculture on climate change while improving productivity and reducing resource use. There is an increasing demand for improved, low cost quantification of GHGs in agriculture, whether for national reporting to the United Nations Framework Convention on Climate Change (UNFCCC), underpinning and stimulating improved practices, establishing crediting mechanisms, or supporting green products. This ERL focus issue highlights GHG quantification to call attention to our existing knowledge and opportunities for further progress. In this article we synthesize the findings of 21 papers on the current state of global capability for agricultural GHG quantification and visions for its improvement. We conclude that strategic investment in quantification can lead to significant global improvement in agricultural GHG estimation in the near term

The FAOSTAT database of greenhouse gas emissions from agriculture

Peer reviewedPublisher PD

A multi-approach software library for estimating crop suitability to environment

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An Integrated Framework to Assess Greenwashing

In this paper we examine definitions of ‘greenwashing’ and its different forms, developing a tool for assessing diverse ‘green’ claims made by various actors. Research shows that significant deception and misleading claims exist both in the regulated commercial sphere, as well as in the unregulated non-commercial sphere (e.g., governments, NGO partnerships, international pledges, etc.). Recently, serious concerns have been raised over rampant greenwashing, in particular with regard to rapidly emerging net zero commitments. The proposed framework we developed is the first actionable tool for analysing the quality and truthfulness of such claims. The framework has widespread and unique potential for highlighting efforts that seek to delay or distract real solutions that are urgently needed today to tackle multiple climate and environmental crises. In addition, we note how the framework may also assist in the development of practices and communication strategies that ultimately avoid greenwashing

An Integrated Framework to Assess Greenwashing

Funding: This research was funded by the Department of Political Science at University of Vienna, Austria and the Institute at Brown for Environment and Society, USA, in association with Climate Social Science Network.Peer reviewedPublisher PD

A new cropland area database by country circa 2020

We describe a new dataset of cropland area circa the year 2020, with global coverage and with data for 221 countries and territories and 34 regional aggregates. Data are generated from geospatial information on the agreement–disagreement characteristics of six open-access high-resolution cropland maps derived from remote sensing. The cropland area mapping (CAM) aggregation dataset provides information on (i) mean cropland area and its uncertainty, (ii) cropland area by six distinct cropland agreement classes, and (iii) cropland area by specific combinations of underlying land cover product. The results indicated that world cropland area is 1500 ± 400 Mha (mean and 95 % confidence interval), with a relative uncertainty of 25 % that increased across regions. It was 50 % in Central Asia (40 ± 20 Mha), South America (180 ± 80 Mha), and Southern Europe (40 ± 20 Mha) and up to 40 % in Australia and New Zealand (50 ± 20 Mha), Southeastern Asia (80 ± 30 Mha), and Southern Africa (16 ± 6 Mha). Conversely, cropland area was estimated with better precision, i.e., smaller uncertainties in the range 10 %–25 % in Southern Asia (230 ± 30 Mha), Northern America (200 ± 40 Mha), Northern Africa (40 ± 10 Mha), and Eastern Europe and Western Europe (40 ± 10 Mha). The new data can be used to investigate the coherence of information across the six underlying products, as well as to explore important disagreement features. Overall, 70 % or more of the estimated mean cropland area globally and by region corresponded to good agreement of underlying land cover maps – four or more. Conversely, in Africa cropland area estimates found significant disagreement, highlighting mapping difficulties in complex landscapes. Finally, the new cropland area data were consistent with FAOSTAT (FAO, 2023) in 15 out of 18 world regions, as well as for 114 out of 182 countries with a cropland area above 10 kha. By helping to highlight features of cropland characteristics and underlying causes for agreement–disagreement across land cover products, the CAM aggregation dataset may be used as a reference for the quality of country statistics and may help guide future mapping efforts towards improved agricultural monitoring. Data are publicly available at https://doi.org/10.5281/zenodo.7987515 (Tubiello et al., 2023a).</p

Maintaining Rice Production while Mitigating Methane and Nitrous Oxide Emissions from Paddy Fields in China: Evaluating Tradeoffs by Using Coupled Agricultural Systems Models

China is the largest rice producing and consuming country in the world, accounting for more than 25% of global production and consumption. Rice cultivation is also one of the main sources of anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. The challenge of maintaining food security while reducing greenhouse gas emissions is an important tradeoff issue for both scientists and policy makers. A systematical evaluation of tradeoffs requires attention across spatial scales and over time in order to characterize the complex interactions across agricultural systems components. We couple three well-known models that capture different key agricultural processes in order to improve the tradeoff analysis. These models are the DNDC biogeochemical model of soil denitrification-decomposition processes, the DSSAT crop growth and development model for decision support and agro-technology analysis, and the regional AEZ crop productivity assessment tool based on agro-ecological analysis. The calibration of eco-physiological parameters and model evaluation used the phenology and management records of 1981-2010 at nine agro-meteorological stations spanning the major rice producing regions of China. The eco-physiological parameters were calibrated with the GLUE optimization algorithms of DSSAT and then converted to the counterparts of DNDC. The upscaling of DNDC was carried out within each cropping zone as classified by AEZ. The emissions of CH4 and N2O associated with rice production under different management scenarios were simulated with the DNDC at each site and also each 1010 km grid-cell across each cropping zone. Our results indicate that it is feasible to maintain rice yields while reducing CH4 and N2O emissions through careful management changes. Our simulations indicated that a reduction of fertilizer applications by 5-35% and the introduction of midseason drainage across the nine study sites resulted in reduced CH4 emission by 17-40% and N2O emission by 12-60%, without negative consequences on rice yield