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Background: This study investigates the long-term effects of agricultural natural gas emissions on ecological footprints across 19 European countries from 2006 to 2020. Employing Cross-Sectional Distributed Lag and Cross-Sectional Autoregressive Distributed Lag models, the research aims to deepen the understanding of agricultural emissions' dynamics and their impact on ecological sustainability. Results: The study reveals that reductions in renewable energy consumption negatively affect ecological footprints, indicating the crucial role of renewable energy adoption in environmental sustainability. The findings emphasize the need for policies that promote renewable energy and address barriers to its adoption. Additionally, the research identifies significant correlations between population growth and ecological footprints, demonstrating the influence of demographic factors on environment. The analysis highlights significant correlations between population growth and ecological footprints, underscoring the importance of demographic trends in shaping environmental policy. Conclusions: The policy implications of this study include advocating for sustainable urban planning and incentivizing eco-friendly agricultural practices to mitigate emissions and promote environmental sustainability. By enhancing our understanding of the relationship between agricultural emissions and ecological footprints, this research provides valuable insights for evidence-based environmental policymaking in European countries. [ABSTRACT FROM AUTHOR]

Abstract Background This study investigates the long-term effects of agricultural natural gas emissions on ecological footprints across 19 European countries from 2006 to 2020. Employing Cross-Sectional Distributed Lag and Cross-Sectional Autoregressive Distributed Lag models, the research aims to deepen the understanding of agricultural emissions’ dynamics and their impact on ecological sustainability. Results The study reveals that reductions in renewable energy consumption negatively affect ecological footprints, indicating the crucial role of renewable energy adoption in environmental sustainability. The findings emphasize the need for policies that promote renewable energy and address barriers to its adoption. Additionally, the research identifies significant correlations between population growth and ecological footprints, demonstrating the influence of demographic factors on environment. The analysis highlights significant correlations between population growth and ecological footprints, underscoring the importance of demographic trends in shaping environmental policy. Conclusions The policy implications of this study include advocating for sustainable urban planning and incentivizing eco-friendly agricultural practices to mitigate emissions and promote environmental sustainability. By enhancing our understanding of the relationship between agricultural emissions and ecological footprints, this research provides valuable insights for evidence-based environmental policymaking in European countries.

Purpose: The study's objective is to assess the environmental performance of rice production in Northern Italy, in particular in Piedmont, the first Italian and European district for the rice-growing area, and thus identify the most critical hotspots and agricultural processes. In particular, as a case study, a farm located in Vercelli (VC) has been chosen. Subsequently, the study results were compared with other different cultivation practices to evaluate the most sustainable choice. Methods: The application of the LCA has been performed, highlighting the phases of rice production that have the most significant impact. Then, uncertainty and sensitivity analyses have been made to estimate the robustness of the results and assess the influence of changing some input variables on emission reduction. Finally, multivariate statistical, specifically a principal component analysis (PCA), was conducted to aid the interpretation of the output dataset of this case study. LCA, uncertainty analysis, and sensitivity analysis were performed with SimaPro 9.2.0, using ReCiPe 2016 Midpoint (H) methodology, and PCA with R software. Results and discussions: The hotspot with the highest environmental load is irrigation, which compared to the other phases impacts more in 15 out of 18 categories, including 12 with impacts greater than + 75%. This is because irrigation causes direct impacts, related to the methanogenesis in rice fields, but also indirect impacts related mainly to the production of the energy mix required to move the large masses of irrigation water. Therefore, different water management systems were compared and results show that the irrigation systems based on intermittent paddy submergence (DSI) could result in − 40% lower impacts, resulting to be the preferable technique over the other irrigation systems analyzed, including the traditional one used in this study. Conclusions: In order to reduce the environmental impacts related to the irrigation process, a water management system characterized by intermittent flooding of the paddy field (DSI) could be used as it reduces the environmental impacts the most (− 40%), while the least suitable system is one characterized by continuous flooding without drought periods, as it causes the highest impacts. [ABSTRACT FROM AUTHOR]

The aim of this study was to highlight the interrelationship between the environmental, social, and economic pillars of agricultural sustainability and their impact on rural development in EU countries. By considering the cumulative influence of 15 social, economic, and environmental indicators, the study clustered the EU countries into five homogeneous groups using principal component analysis and cluster analysis. The research findings confirm that there is a significant trade-off between the three dimensions of sustainability, particularly between the environmental dimension, on the one hand, and the socio–economic dimension, on the other. Thus, the main real challenges identified for the countries included in cluster 5 (Bulgaria, Greece, Croatia, Lithuania, Latvia, Poland, Romania, and Hungary) are related to the socio–economic pillar of sustainability. Moreover, for four EU countries (Netherlands, Belgium, Denmark, and Ireland), included in two different clusters, achieving environmental goals such as reducing agricultural emissions (SDG 2.60) and increasing area under organic farming (SDG 2.40) represents a significant issue in sustainable agriculture. The results highlighted specific challenges to sustainability in agriculture for EU countries that can hinder its effects on rural development. Therefore, tailored measures should be designed to efficiently address these specific issues. [ABSTRACT FROM AUTHOR]

In the European Union, greenhouse gas emissions statistics indicate only a slight decreasing trend over the last number of years in emissions from agricultural sources. Unless drastic action is taken in other sectors, the European Union's 2030 and subsequent climate targets are unlikely to be met without greater reductions made in agricultural emissions. The policy instruments aimed at reducing agricultural emissions that are currently in place have proven to be ineffective; therefore, there is a need to look for new approaches towards bringing agricultural emissions down faster and farther. One obvious new approach is to integrate agricultural emissions into the European Union Emissions Trading System, which, so far, has proven very successful in reducing greenhouse gas emissions in the energy and industrial sectors. Hardly any attention has been paid in the scholarly legal literature to the question of integrating agricultural GHG emissions into emission trading systems. This article seeks to fill this gap. This paper presents the concluding findings of a Dutch Research Council-funded research project that aimed to assess whether and under what conditions the European Union Emissions Trading System could play a role in compelling the agricultural sector to reduce its greenhouse gas emissions. We answered this question by looking at lessons learned from existing examples in the world of market-based approaches to integrating agriculture into emission reduction schemes. To do this, we performed an ex-post assessment of three of the very few examples that exist in the world of such schemes in Canada, California, and Australia, followed by an ex-ante assessment of the prospect of including agricultural emissions under the European Union Emissions Trading System based on the practical experiences of those examples. In the ex-ante study, we evaluated how such inclusion could work, either indirectly, through allowing on-farm offset programs to reward increased carbon sequestration, or directly, by requiring farmers and/or other actors in the agricultural sector to surrender allowances for their direct emissions. As lawyers, we focused mainly on the legal considerations of such a proposition. Having conducted both the ex-ante and ex-post assessments, we conclude that introducing stricter legal instruments of one form or another that will reduce agricultural greenhouse gas emissions and increase carbon removal on agricultural land seems necessary for the European Union if it is serious about achieving its commitments under the Paris Agreement and meeting its obligations under its own Climate Law. The project makes a novel contribution to the legal scholarship in concluding that the most viable starting point for such stricter legislation would be to include methane and nitrous oxide emissions from livestock keeping and synthetic fertilizer use, respectively, under the European Union Emissions Trading System. To start with, this could be conducted by obliging meat and dairy processors and synthetic fertilizer producers to surrender allowances for the on-farm emissions associated with their products. This could be complemented by introducing a voluntary, but still highly regulated, carbon credits scheme that could encourage and reward farmers for reducing their own emissions and for transitioning to net-zero, and overall, more climate-resilient and environmentally friendly farming practices. Such credits could be offered for sale on the private carbon market as well as to Member State governments and the European Commission (through, for example, the Common Agricultural Policy, State Aid schemes, or the Innovation Fund). [ABSTRACT FROM AUTHOR]

Transparent, accurate, comparable, and complete estimates of greenhouse gas emissions and removals are needed to support mitigation goals and performance assessments under the Paris Agreement. Here, we present a comparative analysis of the agriculture forestry and other land use (AFOLU) emission estimates from different datasets, including National Greenhouse Gas Inventories (NGHGIs), FAOSTAT, the BLUE, OSCAR, and Houghton (here after updated H&N2017) bookkeeping models; Emissions Database for Global Atmospheric Research (EDGAR); and the US Environmental Protection Agency (EPA). We disaggregate the fluxes for the forestry and other land use (FOLU) sector into forest land, deforestation, and other land uses (including non-forest land uses), while agricultural emissions are disaggregated according to the sources (i.e., livestock, croplands, rice cultivation, and agricultural fires). Considering different time periods (1990–1999, 2000–2010, and 2011–2018), we analyse the trend of the fluxes with a key focus on the tropical regions (i.e., Latin America, sub-Saharan Africa, and South and Southeast Asia). Three of the five data sources indicated a decline in the net emissions over the tropics over the period 1990–2018. The net FOLU emissions for the tropics varied with values of 5.47, 5.22, 4.28, 3.21, and 1.17 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs, respectively) over the recent period (2011–2018). Gross deforestation emissions over the same period were 5.87, 7.16, 5.48, 3.96, and 3.74 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). The net forestland sink was −1.97, −3.08, −2.09, −0.53, and −3.00 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). Continental analysis indicated that the differences between the data sources are much large in sub-Saharan Africa and South and Southeast Asia than in Latin America. Disagreements in the FOLU emission estimates are mainly explained by differences in the managed land areas and the processes considered (i.e., direct vs indirect effects of land use change, and gross vs net accounting for deforestation). Net agricultural emissions from cropland, livestock, and rice cultivation were more homogenous across the FAOSTAT, EDGAR, and EPA datasets, with all the data sources indicating an increase in the emissions over the tropics. However, there were notable differences in the emission from agricultural fires. This study highlights the importance of investing and improving data sources for key fluxes to achieve a more robust and transparent global stocktake. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas emissions from agriculture is crucial to reach global and regional climate targets. However, the efficiency of unilateral climate policies aimed at taxing emissions might be hampered by carbon leakage. One way to eliminate leakage is to implement a global carbon tax. In this article, we study the effects of a carbon tax in agriculture on GHG emissions by simulating five policy scenarios using the CAPRI model; (i) an EU tax, (ii) an EU tax complemented with a border carbon adjustment mechanism (BCA), (iii) a global tax, (iv) a global tax scaled by GDP per capita, and (v) a low global tax at 1/10 of the tax level in the other scenarios. For the global scenarios, we also analyse the impact on food consumption and nutrient intake. We find that a global tax of EUR 120 per ton CO2-eq could reduce global agricultural emissions by 19%, but also jeopardizes food security in some parts of the world. A global tax at 1/10 of that rate (EUR 12) achieves a 3.2% reduction. In contrast, a unilateral EU tax of EUR 120 per ton CO2-eq, accompanied with a BCA, reduces global agricultural emissions by only 0.15%. A unilateral carbon tax in the EU causes significant emission leakage. This result depends strongly on differences in emission intensities between regions and on consumer preferences. A EUR 12 global carbon tax achieves a considerably larger global emission reduction than a EUR 120 unilateral EU carbon tax accompanied with a border carbon adjustment. A global carbon tax differentiated by GDP per capita is less effective than a uniform global carbon tax, as producers with higher emission intensities tend to get lower tax rates. Other ways of taking equity into account should be sought when designing climate policies in the agricultural sector. [ABSTRACT FROM AUTHOR]

Reducing agricultural emissions is one of the most important issues in global policy, which is becoming increasingly challenging as time goes on. To address this, our study explores the major determinants of agricultural emissions in the Western Balkans while considering gross domestic product (GDP), agriculture value added, trade, energy use in agriculture, and foreign direct investments (FDI). The empirical results based on panel data analysis showed that GDP does not have a significant impact on emissions. Agriculture value added has had a significant and negative impact on nitrous oxide emissions and a significant and positive impact on methane emissions. Trade has significantly negatively affected nitrous oxide and methane emissions, while energy consumption has had a significant and positive impact on nitrous oxide and methane emissions. FDI has had a significant and positive impact on methane emissions, while its effect on nitrous oxide emissions was not statistically significant. This article can serve as a basis for further research on the topic.

Reduced volatile sulfur compounds emitted from e.g. livestock production and biogas production facilities contribute to general air pollution and local odour nuisance. Improved technologies are required to mitigate the emissions of both hydrogen sulfide and organic sulfur compounds. The present study examines the oxidative absorption of reduced sulfur compounds, i.e. hydrogen sulfide, methanethiol and dimethyl sulfide in a wet oxidation process with cupric chloride. It was found that this process efficiently removes both hydrogen sulfide and methanethiol with removal efficiencies >94% under all process conditions tested, while the removal of dimethyl sulfide was in the range 20–40%. The main products determined were dimethyl disulfide, dimethyl trisulfide and elemental sulfur. It was shown that the process was more efficient than the similar process with ferric ions and higher removal could be obtained with lower residence times. Furthermore, though employing cupric ion as metal catalysts results in the production of gaseous sulfur compounds, it is estimated that this process is efficient for deodorization due to the higher odour threshold values of the product compounds and the pH range is optimal for gas streams containing CO2. [ABSTRACT FROM AUTHOR]

Past emission controls in the UK have substantially reduced precursor emissions of health‐hazardous fine particles (PM2.5) and nitrogen pollution detrimental to ecosystems. Still, 79% of the UK exceeds the World Health Organization (WHO) guideline for annual mean PM2.5 of 5 μg m−3 and there is no enforcement of controls on agricultural sources of ammonia (NH3). NH3 is a phytotoxin and an increasingly large contributor to PM2.5 and nitrogen deposited to sensitive habitats. Here we use emissions projections, the GEOS‐Chem model, high‐resolution data sets, and contemporary exposure‐risk relationships to assess potential human and ecosystem health co‐benefits in 2030 relative to the present day of adopting legislated or best available emission control measures. We estimate that present‐day annual adult premature mortality attributable to exposure to PM2.5 is 48,625 (95% confidence interval: 45,188–52,595), that harmful amounts of reactive nitrogen deposit to almost all (95%) sensitive habitat areas, and that 75% of ambient NH3 exceeds levels safe for bryophytes and lichens. Legal measures decrease the extent of the UK above the WHO guideline to 58% and avoid 6,800 premature deaths by 2030. This improves with best available measures to 36% of the UK and 13,300 avoided deaths. Both legal and best available measures are insufficient at reducing the extent of damage of nitrogen pollution to sensitive habitats. Far more ambitious reductions in nitrogen emissions (>80%) than is achievable with best available measures (34%) are required to halve the amount of excess nitrogen deposited to sensitive habitats. Plain Language Summary: Particulate matter pollution is detrimental to human health, nitrogen pollution offsets ecosystem balance of sensitive habitats, and ammonia is toxic to plants. Here we determine the potential public health and ecosystem benefits of adopting currently legislated or best available emission control measures. We use state‐of‐science air quality and exposure assessment models and high‐resolution data sets to estimate air pollution abundances and deposition and determine risk of human and ecosystem harm from air pollution in the UK. We find that substantial improvements to public health result from currently legislated measures, estimated as the number of avoided early deaths attributable to decline in particulate matter pollution. The number of avoided deaths doubles with best available emission control measures, as these also target particulate matter precursor emissions of ammonia from agricultural activity not mandated by existing legislation. The benefits to sensitive habitats of either legal or best available measures is near‐negligible. Mitigating harm to ecosystems will require major advances in emission mitigation technologies. Key Points: Efficacy of required and best available emission control technologies tested with the GEOS‐Chem model and new exposure‐harm relationshipsBoth reduce public exposure to particulate matter pollution and avoid 6,800 adult early deaths with legislation and 13,300 with technologyNeither is sufficient at lessening sensitive habitat exposure to harmful loads of nitrogen and concentrations of phytotoxic ammonia [ABSTRACT FROM AUTHOR]

The aim of this study was to highlight the interrelationship between the environmental, social, and economic pillars of agricultural sustainability and their impact on rural development in EU countries. By considering the cumulative influence of 15 social, economic, and environmental indicators, the study clustered the EU countries into five homogeneous groups using principal component analysis and cluster analysis. The research findings confirm that there is a significant trade-off between the three dimensions of sustainability, particularly between the environmental dimension, on the one hand, and the socio–economic dimension, on the other. Thus, the main real challenges identified for the countries included in cluster 5 (Bulgaria, Greece, Croatia, Lithuania, Latvia, Poland, Romania, and Hungary) are related to the socio–economic pillar of sustainability. Moreover, for four EU countries (Netherlands, Belgium, Denmark, and Ireland), included in two different clusters, achieving environmental goals such as reducing agricultural emissions (SDG 2.60) and increasing area under organic farming (SDG 2.40) represents a significant issue in sustainable agriculture. The results highlighted specific challenges to sustainability in agriculture for EU countries that can hinder its effects on rural development. Therefore, tailored measures should be designed to efficiently address these specific issues.

Abstract Past emission controls in the UK have substantially reduced precursor emissions of health‐hazardous fine particles (PM2.5) and nitrogen pollution detrimental to ecosystems. Still, 79% of the UK exceeds the World Health Organization (WHO) guideline for annual mean PM2.5 of 5 μg m−3 and there is no enforcement of controls on agricultural sources of ammonia (NH3). NH3 is a phytotoxin and an increasingly large contributor to PM2.5 and nitrogen deposited to sensitive habitats. Here we use emissions projections, the GEOS‐Chem model, high‐resolution data sets, and contemporary exposure‐risk relationships to assess potential human and ecosystem health co‐benefits in 2030 relative to the present day of adopting legislated or best available emission control measures. We estimate that present‐day annual adult premature mortality attributable to exposure to PM2.5 is 48,625 (95% confidence interval: 45,188–52,595), that harmful amounts of reactive nitrogen deposit to almost all (95%) sensitive habitat areas, and that 75% of ambient NH3 exceeds levels safe for bryophytes and lichens. Legal measures decrease the extent of the UK above the WHO guideline to 58% and avoid 6,800 premature deaths by 2030. This improves with best available measures to 36% of the UK and 13,300 avoided deaths. Both legal and best available measures are insufficient at reducing the extent of damage of nitrogen pollution to sensitive habitats. Far more ambitious reductions in nitrogen emissions (>80%) than is achievable with best available measures (34%) are required to halve the amount of excess nitrogen deposited to sensitive habitats.

Copyright of Serbian Journal of Management is the property of Serbian Journal of Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

North American nitrous oxide (N2O) emissions over 2011–2018 are estimated using the CarbonTracker‐Lagrange regional inversion framework. Emissions are strongest in the Midwestern corn/soybean belt and display a distinct dual maxima seasonal pattern. The first maximum occurs in late winter/early spring, suggestive of freeze‐thaw (FT) effects on denitrification rates and associated N2O emissions. The second maximum occurs in late spring/early summer, consistent with a growing season nitrogen fertilizer‐driven source, although fertilizer applied in late fall may contribute to the FT pulse as well. Interannual variability in the first maximum correlates significantly to soil freeze thaw status derived from remote sensing data. A requisite frozen period in the preceding early winter appears necessary to create conditions for the N2O pulse after thawing. The FT pulse is a prominent feature of the annual cycle in Canadian cropland, where it may be of comparable magnitude to growing season emissions. In contrast, the growing season peak in N2O dominates the FT peak in the Midwestern Corn‐Soybean region of the United States. Key Points: Early spring peaks in N2O flux from North American agriculture correlate to satellite soil freeze/thaw status from the previous winterA requisite frozen period in early winter appears necessary to prepare the soil for the freeze‐thaw (FT) N2O pulseGrowing season N2O emissions dominate FT emissions in U.S. agriculture but the two have comparable magnitude in Canada [ABSTRACT FROM AUTHOR]

As emissions of nitrogen oxides (NOx) from fossil fuel combustion decrease, the relative contribution of NOx emissions from managed and unmanaged soils (SNOx) is increasing. Modeling SNOx presents a challenge as it requires proper characterization of emission dynamics in response to environmental conditions. SNOx is often represented using the Berkeley Dalhousie Soil NOx Parameterization (BDSNP), which relies upon static relationships between soil moisture and SNOx for arid and non‐arid lands. However, soil chamber and atmospheric studies have shown that emission characteristics are more dynamic, with peak emissions often occurring at higher soil moisture content. Here, to better capture observational studies, we update BDSNP by creating a dynamic SNOx response to soil moisture based on a normalized soil moisture index. We compare the standard and updated parameterizations over the contiguous United States (U.S.) for 2011–2020 using input soil moisture data from ERA5‐Land, MERRA‐2 and NLDAS2‐Mosaic and evaluate SNOx across these different input drivers as well as between the standard and updated parameterizations. The standard parametrization exhibits strong sensitivity to different input soil moisture products, with annual U.S. SNOx differences of up to 0.28 Tg N yr−1. In contrast, the updated parameterization provides a robust representation of SNOx with reduced sensitivity to input soil moisture product with differences of at most 0.03 Tg N yr−1. The updated parameterization simulates a broad increase in SNOx in non‐arid regions, including much of the Eastern U.S., indicating that this region may be more sensitive to climatically‐driven SNOx as anthropogenic NOx emissions continue to decline. Plain Language Summary: Nitrogen oxides (NOx = NO + NO2) are reactive nitrogen gases that have a direct negative impact on health and air quality. While most NOx in the United States derives from fossil fuel combustion, a substantial fraction is released into the atmosphere by microbial processes in the soil. One frequently used model parameterization estimates soil NOx emissions from environmental factors including soil moisture, with a spatially constant relationship between soil NOx and soil moisture despite different soil and ecosystem characteristics. We update this model parameterization to produce variable soil moisture‐NOx relationships for different locations based on local soil moisture history. Unlike the standard parameterization where emissions varied greatly with different soil moisture input datasets, the updated parameterization produces similar results regardless of the soil moisture dataset. The revised soil moisture relationship increases modeled soil NOx emissions over much of the intensively managed cropland across the eastern United States, with potential to influence local and regional air quality. Key Points: A soil NOx emissions (SNOx) parameterization is updated to reflect the dynamic spatial relationships between soil moisture and SNOxThe updated parameterization produces consistent SNOx estimates when using different soil moisture products to drive the modelRegions of the Eastern United States with intensively managed cropland experience the largest increases in SNOx [ABSTRACT FROM AUTHOR]

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.

Tracking agriculture and land-use greenhouse gas (GHG) emissions is necessary to inform global climate policy, yet UNFCCC country-reported data and three independent global databases show inconsistent estimates of countries’ emissions. Data for developing countries are particularly inconsistent, yet also collectively the largest source of emissions. Here, we provide transparency about available country-level emissions data for agriculture and related land use and characterize their data quality and consistency to enable better understanding of available data and tracking of climate change mitigation. We call for increased consistency in official national agricultural GHG inventory data and transparency about the differences among scientific data sources to enable decision makers to track progress, set priorities and manage emissions.

Several policies have been proposed to reduce the environmental impact of agricultural trade. However, a number of these policies have low efficiency on a global scale due to side effects on third-competitor countries. The objective of this article is to assess the consequences of these policies under the existence of market failures that characterise the agricultural sector (i.e., ex ante price uncertainty and oligopoly in international markets). In particular, it is shown that some of these policies could cause instability in the agricultural trade system in the short/medium run, as well as permanent adverse side effects on competitor countries. Using a theoretical dynamic model that includes these failures, it was found that instability could be reduced by supplying information that could help producers to improve price forecasting. Likewise, the adverse side effects could be prevented by means of sustainable policies adopted co-ordinately by competitor countries. This latter result is consistent with the general strategies stated by the Climate Club. [ABSTRACT FROM AUTHOR]

Intensive animal agriculture is an important part of the US and North Carolina's (NC's) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM2.5 chemical composition analysis suggests that ammonium is a major component of the PM2.5 aerosol. [ABSTRACT FROM AUTHOR]

To align business activities with the Paris Agreement goal to limit global warming to 1.5°, companies may disclose and set targets to mitigate their emissions. The global food system contributes up to 37% of total annual emissions. Major food & beverage processing companies heavily contribute to food system emissions through their supply chains. Despite this, sector-specific analysis of the status and quality of scope 3 emissions for food & beverage processing companies is lacking. Using 2018 CDP data to build a sample of 153 companies, the authors describe the state of voluntary disclosure, particularly for scope 3, for food & beverage processing companies. Further, the paper investigated the effect of emissions performance, national environmental policy, international negotiation group, and primary activity on scope 3 disclosure. It also examined the effect of primary activity, scope 3 disclosure, and national environmental policy and international negotiation group on direct- and energy-related emissions performance. The authors found scope 3 disclosure in the food & beverage processing sector was incomplete and inconsistent. The 2018 Environmental Performance Index score and the international negotiating group of a company's headquarter country were significant predictors of scope 3 disclosure by category. Firm size (by revenue) was the only significant predictor of direct and energy-related (scopes 1 and 2) emissions, but was not correlated with improved emissions performance. The authors concluded with a set of recommendations to improve the availability and transparency of scope 3 emissions data, and invited further research into sector-specific scope 3 disclosure, performance, effect of firm size and climate policy at the national and international levels.

Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM2.5 chemical composition analysis suggests that ammonium is a major component of the PM2.5 aerosol.

Copyright of Agronomy Science is the property of University of Life Sciences in Lublin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

New Zealand's primary strategy for tackling greenhouse gas emissions is the emissions trading scheme, which puts a price on emissions from all major industries – except animal agriculture. In the decade since the scheme was introduced, conversations about including emissions from animal agriculture have been shrouded in controversy, with a levy on such emissions dubbed a 'fart tax'. Across two independent samples of New Zealanders, we examined whether support for a charge on farm emissions differed depending on how the charge was framed. We showed that participants were more supportive of including farm emissions in the existing scheme than supporting a 'fart tax', and also that the description of the policy that most closely aligned with the Labour Party's original proposal for the charge (a levy on the agricultural sector to fund research into low carbon farming practices) garnered the most support. Across both samples, support also varied by political affiliation, with support highest among Green voters, followed by Labour voters, and National voters generally opposing the charge, regardless of framing. Frames did not interact with political affiliation in the expected way, suggesting that 'fart tax' referencing reaches across the political divide in undermining support for this policy. [ABSTRACT FROM AUTHOR]

Small-scale farming production systems are integral drivers of global sustainability challenges and the climate crisis as well as a solution space for the transition to climate compatible development. However, mainstreaming agricultural emissions into a climate action agenda through integrative approaches, such as Climate Smart Agriculture (CSA), largely reinforces adaptation–mitigation dualism and pays inadequate attention to institutions’ linkage on the generation of externalities, such as Greenhouse Gas (GHG) emissions. This may undermine the effectiveness of local–global climate risk management initiatives. Literature data and a survey of small-scale farmers’ dairy feeding strategies were used in the simulation of GHG emissions. The effect of price risks on ecoefficiencies or the amount of GHG emissions per unit of produced milk is framed as a proxy for institutional feedbacks on GHG emissions and effect at scale. This case study on small-scale dairy farmers in western Kenya illustrates the effect of local-level and sectoral-level institutional constraints, such as market risks on decision making, on GHG emissions and the effectiveness of climate action. The findings suggest that price risks are significant in incentivising the adoption of CSA technologies. Since institutional interactions influence the choice of individual farmer management actions in adaptation planning, they significantly contribute to GHG spillover at scale. This can be visualised in terms of the nexus between low or non-existent dairy feeding strategies, low herd productivity, and net higher methane emissions per unit of produced milk in a dairy value chain. The use of the Sustainable Food Value Chain (SFVC) analytical lens could mediate the identification of binding constraints, foster organisational and policy coherence, as well as broker the effective mainstreaming of agricultural emissions into local–global climate change risk management initiatives. Market risks thus provide a systematic and holistic lens for assessing alternative carbon transitions, climate financing, adaptation–mitigation dualism, and the related risk of maladaptation, all of which are integral in the planning and implementation of effective climate action initiatives.

Abstract Agricultural emissions strongly contribute to fine particulate matter pollution (PM2.5) and associated effects on human health. Environmentally-extended input-output models and a regional atmospheric chemistry model (WRF-Chem) were combined to conduct an economy-wide assessment of air pollution and pre-mature mortality in the European Union (EU), associated with a 20% increase in the final demand for the output of the agricultural sector. Model results revealed significant differences in air pollution originating from agricultural growth across the 28 EU countries (EU-28). The highest impact of agricultural growth on PM2.5 concentrations occur over the Northern Balkan countries (Bulgaria and Romania) and northern Italy. However, the highest excess mortality rates in the EU-28 due to changes in emissions and enhanced PM2.5 concentrations are observed in Malta, Greece, Spain and Cyprus. The least affected countries are mostly located in the northern part of Europe, with the exception of the Scandinavian Countries, which have relatively good air quality under current conditions. Our integrated modelling framework results highlight the importance of capturing both the direct and indirect air pollution emissions of economic sectors via upstream supply chains and underscore the non-linear response of surface PM2.5 levels and their health impacts to emission fluxes. Graphical abstract Unlabelled Image Highlights • Economic models and WRF-Chem can model agricultural growth effect on air quality. • Agriculture has highest NH 3 and NMVOC emissions per change in economic output in EU. • Shipping has highest SOx, NOx and PM emissions per change in economic output in EU. • Increase in agricultural emissions affects southeastern EU countries most strongly. • 20% agricultural output increase results in 24% increase in excess mortality in EU. [ABSTRACT FROM AUTHOR]

Canadian nitrous oxide (N 2 O) emissions over 2011–2015 are estimated using the CarbonTracker-Lagrange (CT-L) regional inversion. The uncertainty in the whole-country total is high, on the order of 100% or more, with a net flux not significantly different from zero. Emissions are better resolved in Canadian cropland, primarily in Alberta, Saskatchewan, and Manitoba, where the total flux is estimated at 0.08 ± 0.08 Tg N/yr. The uncertainty is improved by the addition of 4 new Canadian sites to the inversion, but remains large, mainly due to the low signal to background ratio at all Canadian N 2 O measurement sites. The seasonal patterns in Canadian cropland emissions suggest a dual maximum, with a late winter freeze-thaw pulse and a growing season flux of similar magnitude. Overall, Canadian cropland accounts for ∼1% of the global anthropogenic N 2 O source according to the inversion, although some process-based models suggest a source more on the order of 2%. • Canadian cropland emits 0.08 ± 0.08 Tg N 2 O–N/yr according to a regional inversion. • This represents ∼1% of the global anthropogenic N 2 O source. • Including 4 new Canadian monitoring sites modestly improves inversion uncertainty. • Canadian cropland N 2 O fluxes have comparable freeze-thaw and growing season peaks. [ABSTRACT FROM AUTHOR]

Globally, agriculture and related land use change contributed about 17% of the world’s anthropogenic GHG emissions in 2010 (8.4 GtCO2e yr−1), making GHG mitigation in the agriculture sector critical to meeting the Paris Agreement’s 2°C goal. This article proposes a range of country-level targets for mitigation of agricultural emissions by allocating a global target according to five approaches to effort-sharing for climate change mitigation: responsibility, capability, equality, responsibility-capability-need and equal cumulative per capita emissions. Allocating mitigation targets according to responsibility for total historical emissions or capability to mitigate assigned large targets for agricultural emission reductions to North America, Europe and China. Targets based on responsibility for historical agricultural emissions resulted in a relatively even distribution of targets among countries and regions. Meanwhile, targets based on equal future agricultural emissions per capita or equal per capita cumulative emissions assigned very large mitigation targets to countries with large agricultural economies, while allowing some densely populated countries to increase agricultural emissions. There is no single ‘correct’ framework for allocating a global mitigation goal. Instead, using these approaches as a set provides a transparent, scientific basis for countries to inform and help assess the significance of their commitments to reducing emissions from the agriculture sector. Key policy insights Meeting the Paris Agreement 2°C goal will require global mitigation of agricultural non-CO2 emissions of approximately 1 GtCO2e yr−1 by 2030. Allocating this 1 GtCO2e yr−1 according to various effort-sharing approaches, it is found that countries will need to mitigate agricultural business-as-usual emissions in 2030 by a median of 10%. Targets vary widely with criteria used for allocation. The targets calculated here are in line with the ambition of the few countries (primarily in Africa) that included mitigation targets for the agriculture sector in their (Intended) Nationally Determined Contributions. For agriculture to contribute to meeting the 2°C or 1.5°C targets, countries will need to be ambitious in pursuing emission reductions. Technology development and transfer will be particularly important. [ABSTRACT FROM AUTHOR]

This paper evaluated the effect of agricultural input (fertilizer) on carbon emission (methane and nitrous oxide) in South Africa and the likely environmental costs of such emissions. The paper applied a quantitative research design and data were from secondary sources, mainly from the archives of Index Mundi, the US EPA and the World Bank. The Pearson correlation results show that fertilizer input is related to agricultural nitrous oxide and methane emissions at a P-value of 0.027 and 0.05 respectively. This thus, confirms that fertilizer input causes an agricultural induced emission of greenhouse gases (nitrous oxide and methane). Furthermore, findings from the estimation of potential environmental costs of methane and nitrous oxide emissions showed that these have had rising and steady environmental costs to the society, which, unfortunately is born by the society. Consequently, the study recommends agricultural related emission policy to enable farmers internalise some of the environmental costs of agricultural inputs that are born by the society, which is the socioeconomic costs. Such further research should determine a fair model that may be used to internalise environmental costs of agricultural inputs but to avoid consumers of agricultural produce from paying for such costs. [ABSTRACT FROM AUTHOR]

Land use change has impacts upon many natural processes, and is one of the key measures of anthropogenic disturbance on ecosystems. Agricultural land covers 70% of Great Britain's (GB) land surface and annually undergoes disturbance and change through farming practices such as crop rotation, ploughing and the planting and subsequent logging of forestry. It is important to quantify how much of GB's agricultural land undergoes such changes and what those changes are at an annual temporal resolution. Integrated Administration and Control System (IACS) data give annual snapshots of agricultural land use at the field level, allowing for high resolution spatiotemporal land use change studies at the national scale. Crucially, not only do the data allow for simple net change studies (total area change of a land use, in a specific areal unit) but also for gross change calculations (summation of all changes to and from a land use), meaning that both gains and losses to and from each land use category can be defined. In this study we analysed IACS data for GB from 2005 to 2013, and quantified gross change for over 90% of the agricultural area in GB for the first time. It was found that gross change totalled 63,500 km 2 in GB compared to 20,600 km 2 of net change, i.e. the real year-on-year change is, on average, three times larger than net change. This detailed information on nature of land use change allows for increased accuracy in modelling the impact of land use change on ecosystem processes and is directly applicable across EU member states, where collection of such survey data is a requirement. The modelled carbon flux associated with gross land use change was at times >100 Gg C y −1 larger than that based on net land use change for some land use transitions. [ABSTRACT FROM AUTHOR]

Agricultural GHG mitigation policies are important if ambitious climate change goals are to be achieved, and have the potential to significantly lower global mitigation costs [Reisinger, A., Havlik, P., Riahi, K., van Vliet, O., Obersteiner, M., & Herrero, M. (2013). Implications of alternative metrics for global mitigation costs and greenhouse gas emissions from agriculture.Climatic Change,117, 677–690]. In the post-Paris world of ‘nationally determined contributions’ to mitigation, the prospects for agricultural mitigation policies may rest on whether they are in the national economic interest of large agricultural producers. New Zealand is a major exporter of livestock products; this article uses New Zealand as a case study to consider the policy implications of three global policy scenarios at the global, national and farm levels. Building on global modelling, a model dairy farm and a model sheep and beef farm are used to estimate the changes in profit when agricultural emissions are priced and mitigated globally or not, and priced domestically or not, in 2020. Related to these scenarios is the metric or GHG exchange rate. Most livestock emissions are non-CO2, with methane being particularly sensitive to the choice of metric. The results provide evidence that farm profitability is more sensitive to differing international policy scenarios than national economic welfare. The impact of the choice of metric is not as great as the impact of whether other countries mitigate agricultural emissions or not. Livestock farmers do best when agricultural emissions are not priced, as livestock commodity prices rise significantly due to competition for land from forestry. However, efficient farmers may still see a rise in profitability when agricultural emissions are fully priced worldwide. Policy relevance Exempting agricultural emissions from mitigation significantly increases the costs of limiting warming to 2 °C, placing the burden on other sectors. However, there may be a large impact on farmers if agricultural emissions are priced domestically when other countries are not doing the same. The impacts of global and national climate policies on farmers need to be better understood in order for climate policies to be politically sustainable. Transitional assistance that is not linked to emission levels could help, as long as the incentives to mitigate are maintained. In the long run, efficient farmers may benefit from climate policy; international efforts should focus on mitigation options and effective domestic policy development, rather than on metrics. [ABSTRACT FROM PUBLISHER]

Ammonia (NH 3 ) deposition in natural areas is a pollution problem that is suited for spatially differentiated pollution control. The heterogeneous impact of nitrogen deposition from airborne ammonia emissions could serve as the basis for differentiated policy measures. Maps were developed that show the potential impact of ammonia emissions on protected Natura 2000 sites in Flanders, Belgium. These maps link the output of atmospheric dispersion and deposition models with data on the nitrogen sensitivity of protected habitats in the Natura 2000 network. The maps demonstrate that the indicator used for impact assessment is a crucial factor in the design of the spatially differentiated policy. The currently used impact indicator in Flanders, the Significance Score, was compared with the Aggregate Deposition Score, an alternative that is a better reflection of the total damage caused by airborne ammonia emissions in nearby Natura 2000 sites. Both indicators are based on the ratio of ammonia deposition to the critical load of nitrogen of the impacted habitat. Spatial effects related to the choice of impact indicator were evaluated. The results indicate that the choice of impact indicator has a decisive role in the geographical outcome of spatially differentiated policies. [ABSTRACT FROM AUTHOR]

Agriculture significantly contributes to greenhouse gas emissions and thus to climate change, directly through farm operations and indirectly through the energy needed to produce input materials, most prominently fertiliser, as well as through nitrous oxide (N 2 O) emissions from soils. Agriculture is the largest consumer of phosphorus, which is a non-renewable resource. Cotton accounts for one third of all natural and synthetic fibres of the total textile production. Today, Xinjiang, China, has become one of the most important cotton producers with highest yields worldwide. The aim of this study was to calculate the carbon ( climate footprint and energy footprint ) and phosphorus footprint of this high yielding cotton production and compare it to a theoretical production of an alternative fibre from Apocynum (local name: Kendyr or Kutra), which is a bast fibre plant native in Xinjiang and Central Asia. The data of the cotton production was collected through farm interviews during six years in Xinjiang. The data for Apocynum was compiled by literature from field experiments in the former Soviet Union. Cotton fibres, mainly due to high fertiliser inputs, caused a climate footprint of 4.43 kg CO 2e /kg fibre, an energy footprint of 30.90 MJ/kg fibre, and a phosphorus footprint of 101 g P/kg fibre. The footprints of Apocynum are significantly lower with a climate footprint of 1.93 kg CO 2e /kg fibre, an energy footprint of 21.85 MJ/kg fibre, and a phosphorus footprint of 1.6 g P/kg fibre. In cotton production, 63.9% of the climate footprint and 68.4% of the energy footprint are attributed to fertiliser production. Soil emissions of N 2 O account for another 22.2% of the climate footprint of cotton. The biggest potential to reduce carbon and phosphorus footprints of cotton production lie in reduced fertiliser application and re-use of plant residues. In the case of Apocynum , 65.1% of the climate footprint and 64.1% of the energy footprint are attributed to chemical treatment of the fibres in the extraction process. [ABSTRACT FROM AUTHOR]

Agriculture takes a large proportion of greenhouse gas (GHG) emissions, playing an essential role in achieving global climate goals. However, targeted mitigation opportunities for agricultural GHG are still unclear due to the lack of standalone analyses at sub-national and food-specific scales. Here, we accounted for agricultural GHG emissions in 2000–2020 in mainland China and found that the largest emission sources by region, product group, process, and gas were Hunan province, rice cultivation, enteric fermentation, and CH 4 , respectively. Agricultural emissions peaked in 2015 and temporarily declined by 8% by 2020 and possibly decline by 30–36% by 2060, primarily owing to the reduction potential from meat production in eastern and northern China. The emissions produced and land needed per unit of food product reduced mostly, while emissions per unit of land use increased in many regions and food groups. We conclude that the opportunities and challenges for GHG mitigation lie in a few top emitters in central China where intensities were unexpectedly much larger than the levels of the national average and marginal agriculture in the northeast. [ABSTRACT FROM AUTHOR]

Ever since 2012, the EU ETS (European Union’s Emission Trading Scheme), which is the EU’s climate policy was extended to include the ESD (Effort Sharing Decision) sectors’ (agriculture, transport, building) regulations. As its name implies, this mechanism is based off of shared interests and efforts, all in order to reach the climate goals. Therefore, analysing the agriculture sector from an environmental viewpoint requires the analysis of related sectors as well, since their performances will have an impact on determining the requirements to be met by the agriculture. Seeing that those primarily present in said sectors are not various firms, but people and public utility management institutions instead, the level of regulations draws from the economic state of the various countries in question (GDP per capita). Therefore, member states like ours did not receive difficult goals until 2020, due to our performance being lower than the average of the EU. However, during the program phase between 2021 and 2030, all nations are to lower their GHG (greenhouse gases) emission, and have to make developments to restrict GHG emission level growth within the ESD, which means we already have to estimate our future possibilities. During the analyses, we will see that analysing agriculture from an environmental viewpoint, without doing the same to their related sectors and their various related influences is impossible. The GHG emission goals determined by the EU have to be cleared by the agriculture sector, but the inputs from transport, waste management and building are required nonetheless. JEL classification: Q58