Agricultural intensification scenarios, household food availability and greenhouse gas emissions in Rwanda: Ex-ante impacts and trade-offs

Climate-smart livestock production at landscape level in Kenya

The increase in greenhouse gas (GHG) emissions is a global concern due to its impact on climate change. To address this challenge, the development of corporate GHG inventories is crucial, enabling organizations to understand and mitigate their emissions. This study aims to statistically analyze whether there was a significant increase in GHG emissions over a 10-year period by organizations from various sectors of the economy that voluntarily published their inventories in the Brazilian GHG Protocol Program. Data were obtained from the inventories of 66 organizations that published at 2013 and 2022 in the Brazilian GHG Protocol Program. The data was processed and analyzed using Minitab software to determine the significance level of the increase in GHG emissions. A total increase of 159,264,734.26 tCO2e in GHG emissions was observed from 2013 to 2022, with 29 organizations reporting higher emissions and 37 showing reductions. However, statistical analysis demonstrated that there was no significant increase in GHG emissions over the study period. The results highlight the importance of organizations conducting their GHG inventories to enhance transparency and make strategic decisions aimed at mitigating their emissions. Publishing inventories allows for monitoring progress and identifying priority areas for effective interventions. No significant increase in GHG emissions was observed over the 10-year period; therefore, this study reinforces the importance of preparing GHG inventories by organizations. The findings can impact public policies on climate change, supporting the introduction of regulations that mandate the development of inventories and the setting of emission reduction and offsetting targets.

Agriculture sector holds an essential role in Latvia’s economy and play significant role in keeping rural areas as a habitable environment (approximately 32 % of the population lives in rural areas). The agricultural sector is responsible for 28.5 % (2018) of total non-European Union Emissions Trading System (non – EU ETS) greenhouse gas (GHG) emissions in Latvia. The largest part of emissions is related to agricultural soils (59.3 %) and enteric fermentation 32.6 % (mainly dairy and beef cattle). The GHG emissions trend of recent years shows a gradual and steady increase in GHG emissions for example between 2005 and 2018 +12.5 % and during the period 2013–2018 emissions increased by 2.12 %. According to Latvia’s National Energy and Climate Plan 2021–2030 (NECP), total GHG emissions in the agricultural sector are expected to increase in the period from 2020 to 2030, mainly in the enteric fermentation and agricultural soil categories. To achieve determined targets for Latvia’s non-EU ETS sector in 2030 and be on track to reach climate neutrality in 2050, the agricultural sector has to contribute to GHG emission mitigation. For the agricultural sector, improved food security and climate smart activities will be necessary to achieve GHG emission reduction. Existing policies and measures (WEM) as well as those which are included in the NECP as additional measures (WAM) were used to assess more suitable measures to move on climate smart agriculture (CSA), that could help to decrease GHG emissions at the farm and state level as well as is expected to contribute towards achieving the commitments in the plan. To achieve the aim of the study, a combination of the Delphi method together with multi-criteria analysis (MCA) is utilized to find a set of top GHG mitigation measures in the future. Results show that, in the future, the measure support the development of innovative technologies and solutions to promote resource efficiency in agriculture is essential to move on climate smart agriculture.

Many agricultural regions in China are likely to become appreciably wetter or drier as the global climate warming increases. However, the impact of these climate change patterns on the intensity of soil greenhouse gas (GHG) emissions (GHGI, GHG emissions per unit of crop yield) has not yet been rigorously assessed. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, we found that climate change is expected to cause a 20.0% crop yield loss, while stimulating soil GHG emissions by 12.2% between 2061 and 2090 in China's agricultural regions. A wetter‐warmer (WW) climate would adversely impact crop yield on an equal basis and lead to a 1.8‐fold‐ increase in GHG emissions relative to those in a drier‐warmer (DW) climate. Without water limitation/excess, extreme heat (an increase of more than 1.5°C in average temperature) during the growing season would amplify 15.7% more yield while simultaneously elevating GHG emissions by 42.5% compared to an increase of below 1.5°C. However, when coupled with extreme drought, it would aggravate crop yield loss by 61.8% without reducing the corresponding GHG emissions. Furthermore, the emission intensity in an extreme WW climate would increase by 22.6% compared to an extreme DW climate. Under this intense WW climate, the use of nitrogen fertilizer would lead to a 37.9% increase in soil GHG emissions without necessarily gaining a corresponding yield advantage compared to a DW climate. These findings suggest that the threat of a wetter‐warmer world to efforts to reduce GHG emissions intensity may be as great as or even greater than that of a drier‐warmer world.

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

Quantifying the impact of energy consumption sources on GHG emissions in major economies: A machine learning approach

Dairy development provides substantial economic opportunities for smallholder crop-livestock farmers in East Africa, but productivity is constrained by scarcity of quantity and quality feed. Livestock is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, loss of biodiversity and land degradation. Improved livestock feeding has been proposed as a triple-win strategy towards achieving climate-smart agriculture, increasing food security and climate change adaptation, and decreasing GHG intensities. Improved tropical forages include a wide variety of sown or planted annual and perennial grasses, herbaceous or dual-purpose legumes and shrubs developed for increasing productivity of grazed and cut-and-carry fed livestock. This thesis aims to explore potential impacts and trade-offs associated with the implementation of improved livestock feeding and forage technologies at farm scale, across a diversity of smallholder crop-livestock systems in East Africa. We first quantitatively reviewed 73 published studies to take stock of evidence on agronomic, livestock, environmental and economic impacts of tropical forage technologies in Sub-Saharan Africa. We then introduced a relatively simple approach to quantify feeding systems and feed gaps in data-scarce smallholder systems. Based on this, household-level impacts and trade-offs of improved livestock feeding and forages were explored in Tanzania and Rwanda, considering productivity, environmental and livelihood dimensions. To do so, a combination of approaches and methods was employed, including coupled livestock and economic modeling, bio-economic farming systems modeling and multi-objective optimization, multi-variate statistics, on-farm monitoring and measurements, semi-structured interviews, participatory validation and expert knowledge. Results from this thesis confirmed the considerable feed gaps in metabolizable energy and crude protein. Feed gap here is defined as the difference between livestock feed demand for an attainable milk production level (attainable feed demand) and actual feed supply at individual herd level. The literature review revealed that higher herbage production and quality of improved forage technologies resulted in an average 35% milk and 24% manure increase and 60% higher associated food crop yields while almost halving soil loss. In Lushoto in Tanzania, predicted adoption rates for improved livestock feeding and poverty reduction among households with improved dairy cows were likely to be higher compared to households with only local cows. Methane emissions intensity declined with adoption of improved livestock feeding strategies. Across Rwanda, livestock production was among the most important pathways to higher food availability. Total baseline GHG emissions were low, with enteric fermentation and manure emissions contributing 74 – 81%. Scenario assessment of three policy options showed that Girinka program (providing a crossbred cow to a poor households) strongly increased food availability of the poorest section of the household population at a high GHG cost, while improved livestock feeding had less impact on food availability but at an only small GHG increase. In Babati in Tanzania, emission intensity was lowest for the dairy farming system (2.1 kg CO2e kg-1 milk) when compared to three other smallholder livestock types, with lowest trade-offs with household income, and carbon and nitrogen balances. Available options to reduce agro-environmental trade-offs included reducing ruminant numbers, replacing local cattle with improved dairy breeds, improve feeding through on-farm forage cultivation to reach higher milk production levels, and reducing crop residue feeding to leave them on the field. However, adoption of these technologies require a skillful re-organization of the entire production system, resulting in loss of some multi-functionality of livestock, and incur higher production risks. In conclusion, we argue that pathways to sustainable intensification of livestock in East Africa are needed, which can also unlock new financing avenues. Improved forages can play a key role as they deliver multiple productivity, economic and environmental benefits when skillfully integrated in smallholder cropping and farming systems. Livestock feeding and forages are thus at multiple crossroads: at a point where crucial decisions regarding future pathways are taken, where productivity and environmental impacts meet, and where scientific disciplines including agronomy, soil and animal science intersect. Results from this thesis aim to inform policy makers, project designers, investors, donors and other decision-makers on prioritizing options towards low emission livestock development. Suggestions and recommendations for future research include next-level forage agronomy, further multi-disciplinary and systems-level trade-off analysis, and quantification of technology contributions to national-level climate and land restoration policy targets.

Trajectory, driving forces, and mitigation potential of energy-related greenhouse gas (GHG) emissions in China's primary aluminum industry

The world population is expected to grow to about 10 billion in 2050. To supply the future human population with food while sustaining a liveable planet, food should be produced sustainably. One of the most urgent environmental issues is climate change, induced by greenhouse gas (GHG) emissions. The dairy sector is a large contributor to GHG emissions. Important GHGs related to milk production are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), mainly emitted during feed production, enteric fermentation, and manure management. Diseases in dairy cows can reduce milk production, reproduction performance and longevity, and increase the amount of discarded milk. The objectives of this thesis were to estimate the impact of diseases (subclinical ketosis, clinical mastitis, and foot lesions) on GHG emissions, and to understand the relation between impact of diseases on GHG emissions and economic performance. First, a dynamic stochastic simulation model was developed to simulate the dynamics of the diseases and the associated production losses (reduced milk production, discarded milk, a prolonged calving interval, and removal (culling or dying on the farm)) per cow during one lactation. This model was combined with a life cycle assessment to quantify the impact of diseases on GHG emissions per ton fat-and-protein-corrected milk (kg CO2equivalents/t FPCM) from cradle to farm gate. Processes included were feed production, enteric fermentation, and manure management. The emissions of GHGs of cows with a disease increased on average by 21 (2.3%) kg CO2e/t FPCM per case of subclinical ketosis, by 58 (6.2%) kg CO2e/t FPCM per case of clinical mastitis, by 4 (0.4%) kg CO2e/ t FPCM per case of digital dermatitis, by 39 (4.3%) kg CO2e/ t FPCM per case of white line disease, and by 33 (3.6%) kg CO2e/ t FPCM per case of sole ulcer. An economic analyses was performed to estimate the costs of subclinical ketosis and related diseases. The total costs of subclinical ketosis were €130 per case per year. Comparing the impact of production contributors from a GHG emissions and economic perspective showed that a reduction in milk production had the highest impact on the economic performance, whereas removal and discarded milk had the highest impact on increase in GHG emissions. Prevalence, pathogen type, farm management (e.g. culling, feed, and manure), and prices (e.g. milk and feed) will affect the impact of production contributors on GHG emissions and economic performance. Therefore, specific farm analyses are needed to estimate the impact of diseases for a specific dairy farm. Diseases in dairy cows increase GHG emissions by approximately 0.4 Mton per year, which equals 15% of the Dutch governmental goal of GHG emission reductions in agriculture in 2030. Reducing diseases can decrease GHG emissions, can increase the income of the farmer, and can improve animal welfare. Therefore, reducing diseases can contribute to sustainable development of the dairy sector.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

PDF HTML阅读 XML下载 导出引用 引用提醒 西安市温室气体排放的动态分析及等级评估 DOI: 10.5846/stxb201305271199 作者: 作者单位: 陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院 作者简介: 通讯作者: 中图分类号: 基金项目: 陕西省软科学研究计划项目(2012KRM48);国家社会科学基金项目(14XKS019);黄土高原土壤侵蚀与旱地农业国家重点实验室基金(10501-1214) Dynamic analysis of greenhouse gas emission and evaluation of the extent of emissions in Xi'an City, China Author: Affiliation: College of Tourism and Environmental Sciences, Shaanxi Normal University,,,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为了解西安市温室气体排放的动态规律和排放水平,基于全球标杆的温室气体排放等级评价方法,并采用国际公认的《2006年IPCC国家温室气体清单指南》和基于IPCC的《省级温室气体编制指南》推荐的方法对西安市的温室气体排放进行了动态分析和排放等级评估。结果表明,从1995年到2011年,西安市温室气体排放呈快速上升趋势,16年间温室气体排放量从1207.16×104t 上升为3934.17×104t,年均增高7.66%。增幅最高的是水泥温室气体(年均增高11.75%)、废弃物(8.77%)和能源(7.63%),农业年均降低1.74%,林业固碳年圴增加3.56%。从温室气体构成看,能源占80.13%-90.55%,水泥占1.75%-7.49%,农业占1.86%-8.01%,林业固碳占-2.58%—5.22%,废物处理占7.52%-16.38%。可见能源消费的增加是导致西安市温室气体排放增长的主要原因,林业碳汇能力有待提高。万元GDP温室气体排放不断降低,说明西安市碳减排方面的科技进步在不断提高。人均、单位面积温室气体排放量和排放指数增速很快,年均增幅分别达5.84%、7.66%和6.84%。西安市温室气体排放等级持续增高,16年间从较低等级(Ⅰc)上升为中下等级(Ⅱa),目前距应对气候变暖目标(Ⅰb)已高出两个亚级,温室气体排放增高的趋势不容忽视。 Abstract:Global warming caused by greenhouse gas emission may cause severe environmental and social problems. Greenhouse gas accounting has become a hotly debated research topic. Internationally, some research has been undertaken on greenhouse gas accounting and some progress has been made; however, there are many shortcomings in this field. The main problem is that current research is mainly focused on carbon emission, particularly carbon emission from fossil fuel combustion, and is less involved in carbon fixation and ways of assessing regional carbon emission levels. In addition, the actual emission figures for greenhouse gases nationally and regionally in China were unknown. Although much research relates to carbon emission, the results are difficult to compare owing to inconsistent research methods and standards. Xi'an City, a historical and cultural tourist city in China, lies in the radiation center of the Guan-Tian economic zone. It is the economic, cultural, education, manufacturing and high-tech industry hub of northwest China. Xi'an will be an international metropolis in China in the near future. However, research relating to the greenhouse gas footprint in Xi'an is scarce. In this paper, the author proposed an evaluation system for greenhouse gas (GHG) emission to the level of global benchmarking using the methods recommended by the 2006 IPCC Guidelines for National Greenhouse Gas Inventories and the Chinese Guidelines for Provincial Greenhouse Gas Inventories, and using this a dynamic analysis of GHG emission and evaluation of the extent of GHG emission in Xi'an City was performed. The results showed that, from 1995 to 2011, GHG emission showed a rapidly rising trend in Xi'an City, increasing from 1207.16×104t to 3934.17×104t, which represented an average annual increase of 7.66%. The largest increase was for cement (an average annual increase of 11.75%), waste (8.77%) and energy (7.63%) GHG. Agricultural GHG emission showed an annual reduction of 1.74%, while forestry carbon sequestration showed an annual average increase of 3.56%. In a breakdown of emissions, energy GHG accounted for 80.13%-90.55%, cement GHG for 1.75%-7.49%, agricultural GHG for 1.86%-8.01%, forestry carbon sequestration for -2.58%—5.22%, and waste treatment GHG for 7.52%-16.38%. An increase in energy consumption is the main cause of the increase in GHG emission in Xi'an City, and forestry carbon sequestration capacity needs to be improved. In Xi'an City, the GHG emission per 10,000 Yuan GDP was constantly decreasing, and progress in the science and technology of carbon emission has continuously improved. The GHG emission per capita, per unit area and per carbon emission index has increased very quickly, showing an average annual increase of 5.84%, 7.66% and 6.84% respectively. The carbon emission state in Xi'an City has increased continually from a low level (Ⅰc) to a middle level (Ⅱa), which was an increase of two sub-grades and which was two grades higher than the target set for the control of global climate warming. The increasing trend in carbon emission cannot be ignored. 参考文献 相似文献 引证文献

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

Greenhouse gases (GHGs) are one of the leading causes of global warming. Therefore, accuracy estimates for greenhouse gases (GHGs) emissions are a key element in defining the best strategies for reducing GHG emissions from various source sectors of the economy. In the present study, an initial attempt has been made to estimate and forecast the GHG emissions in Pakistan from five major sectors, such as energy, industrial, agriculture, waste, and land-use change and forestry. The data were taken from the official website of the Pakistan climate database from 1990 to 2016. We employed advanced mathematical modeling, namely a non-homogenous discrete grey model (NDGM), to predict sector-wise GHGs emissions. Moreover, the present study is a milestone in the GHGs growth analysis by utilizing the synthetic relative growth rate (SRGR) and synthetic doubling time model (SDTM). The results reveal that the industry and land-use change and forestry contribute more in terms of increasing GHGs emissions till 2024, whereas agriculture and waste required comparatively less time to reduce GHGs emissions double in number among five sectors. All five sectors show an increasing trend in forecasting GHGs emissions between 1990 and 2016. However, the results indicate that land-use change and forestry and industrial sectors are more likely to be a reason for the increase in GHGs emissions in the future, followed by the agriculture, energy, and waste sectors. The land-use change and forestry was found prone to increase emission in the future, and the doubling time ( $${D}_{\mathrm{t}}$$ ) suggests less time expected to reduce GHGs. Finally, the study has suggested some policies for the policymakers, government, and decision-makers to reduce GHGs emissions and achieve sustainable development.