Optimizing rice-crayfish systems with direct seeding: Impacts on greenhouse gas emissions and economic performance

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.

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

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.

This paper analyzes how a firm’s management of greenhouse gas (GHG) emissions affects its economic performance. The theoretical model we derive from Cobb–Douglas production and inverse demand functions predict that in conducting GHG emissions management, a firm will enhance its economic performance because it promotes an increase in demand for its output and improves its productivity. The estimation results, using panel data on Japanese manufacturing firms during the period 2007–2008, support the view that a firm’s GHG emissions management enhances a firm’s economic performance through an increase in demand and improvement in productivity. However, the latter effect is conditional. Although a firm’s efforts to maintain lower GHG emissions improves productivity, efforts to reduce GHG emissions further does not always improve it, especially for energy-intensive firms. Because firms attempting to maintain lower GHG emissions are more likely to improve their productivity, there is a possibility that firms with high GHG emissions can also enhance economic performance by reducing their emissions in the long term, even if additional costs are incurred. In addition, better GHG emissions management increases the demand of environmentally conscious customers because a product’s life cycle GHG emissions in the upper stream of the supply chain influence those in the lower stream, and customers evaluate the suppliers’ GHG emissions management in terms of green supply-chain management.

Multiobjective optimization of economic and environmental performance of Fischer-Tropsch biofuels production integrated to sugarcane biorefineries

SUMMARYIn Ireland, the largest contributor of greenhouse gas (GHG) emissions is agriculture. The objective of the current study was to evaluate the impact of stocking intensities of beef cattle production systems on technical and economic performance and GHG emissions. A bioeconomic model of Irish suckler beef production systems was used to generate scenarios and to evaluate their technical and economic performance. To model the impact of each scenario on GHG emissions, the output of the bioeconomic model was used as an inventory analysis in a life-cycle assessment model and various GHG emission factors were integrated with the production profile. All the estimated GHG emissions were converted to their 100-year global warming potential carbon dioxide equivalent (CO2e). The scenarios modelled were bull/heifer and steer/heifer suckler beef production systems at varying stocking intensities. According to policy constraints, stocking intensities were based on the excretion of organic nitrogen (N), which varied depending on animal category. Stocking intensity was increased by increasing fertilizer N application rates. Carcass output and profitability increased with increasing stocking intensity. At a stocking intensity of 150 kg N/ha total emissions were lowest when expressed per kg of beef carcass (20·1 kg CO2e/kg beef) and per hectare (9·2 tCO2e/ha) in the bull/heifer system. Enteric fermentation was the greatest source of GHG emissions and ranged from 0·49 to 0·47 of total emissions with increasing stocking intensity for both production systems. The current study shows that increasing stocking intensity via increased fertilizer N application rates leads to increased profitability on beef farms with only modest increases in GHG emissions.

Relating the carbon footprint of milk from Irish dairy farms to economic performance

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

This paper analyzes how a firm fs reduction of its greenhouse gas (GHG) emissions affects its economic performance. The theoretical model used is derived from the Cobb-Douglas production function and the inverse demand function, and predicts that in reducing its GHG emissions, a firm will increase its value added because it promotes an increase in demand for its output and improves its productivity. The estimation results, using data on Japanese manufacturing firms, suggest that the reduction of GHG emissions increases a firm fs economic performance only through an increase in demand. Thus, firms can improve their overall economic performance because increased demand accompanies their reduction of GHG emissions, even if they cannot achieve this through an improvement in productivity, as estimates here support the traditional view that reducing GHG emissions imposes additional costs on firms.

Increasing oil palm plantations, both for obtaining crude palm oil (CPO) and for the production of biobased products, have generated growing concern about the impact of greenhouse gas (GHG) emissions on the environment. Colombia has the potential to produce sustainable biobased products from oil palm. Nevertheless, national GHG emissions have not yet been reported by this sector. Achieving the collection of the total primary data from the oil palm sector, in Colombia, entails a tremendous challenge. Notwithstanding, for this study, the data collection of 70% of the production of fresh fruit bunches (FFB) was achieved. Therefore, current situation of CPO production in Colombia is analyzed, including 1) GHG emissions calculation, 2) net energy ratio (NER), and 3) economic performance. Moreover, the analysis includes two future scenarios, where the CPO production chain is optimized to reduce GHG emissions. Future scenario A produces biodiesel (BD), biogas, cogeneration, and compost; while future scenario B produces BD, biogas, cogeneration, and pellets. The methodology, for all the scenarios, includes life-cycle assessment and economic analysis evaluation. The results show a significant potential for improving the current palm oil production, including a 55% reduction in GHG emissions. The impact of land-use change must be mitigated to reduce GHG emissions. Therefore, a sustainable oil palm expansion should be in areas with low carbon stock or areas suitable/available to the crop (e.g., cropland, pastureland). Avoiding the deforestation of natural forests is required. Besides, crop yield should be increased to minimize the land use, using biomass to produce biobased products, and capture biogas to reduce methane emissions. In the biodiesel production life-cycle, the NER analysis shows the fossil energy consumed is lower than the renewable energy produced. Regarding the economic performance, it shows that in an optimized production chain, the capital expenditure and operational expenditure will decrease by approximately 20%.

Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

This study aims to determine the effect of greenhouse gas (GHG) emissions on economic performance in terms of energy costs for an industrial wastewater treatment plant. Also, the mitigation of GHG emissions aimed at using process modification to obtain possible reductions in energy costs. Optimum energy consumptions were reported for the minimum GHG emission using the Data Envelopment Analysis (DEA) and Monte Carlo simulation model. In this paper, a new empirical approach has been developed depending on the GHG emissions for estimating the economic performance of the wastewater treatment plants. The results revealed that nitrous oxide (N2O) emissions led to the highest energy costs among direct emissions. In the second stage of the study, the effects of design conditions on GHG emissions and energy costs were investigated. If the aeration tank is operated at 24 h of hydraulic retention time (HRT) and 22 days of solid retention time (SRT), then, on average, 27, 27.9, and 30.7% of reduction in energy costs in terms of direct carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions, respectively, is observed in the plant. These reductions corresponded to approximately 17.33 €/kWh of cost-saving in this plant.

Biomass feedstock can be used for the production of biofuels or biobased chemicals to reduce anthropogenic greenhouse gas (GHG) emissions. Earlier studies about the techno‐economic performance of biofuel or biobased chemical production varied in biomass feedstock, conversion process, and other techno‐economic assumptions. This made a fair comparison between different industrial processing pathways difficult. The aim of this study is to quantify uniformly the factory‐gate production costs and the GHG emission intensity of biobased ethanol, ethylene, 1,3‐propanediol (PDO), and succinic acid, and to compare them with each other and their respective fossil equivalent products. Brazilian sugarcane and eucalyptus are used as biomass feedstock in this study. A uniform approach is applied to determine the production costs and GHG emission intensity of biobased products, taking into account feedstock supply, biobased product yield, capital investment, energy, labor, maintenance, and processing inputs. Economic performance and net avoided GHG emissions of biobased chemicals depend on various uncertain factors, so this study pays particular attention to uncertainty by means of a Monte Carlo analysis. A sensitivity analysis is also performed. As there is uncertainty associated with the parameters used for biobased product yield, feedstock cost, fixed capital investment, industrial scale, and energy costs, the results are presented in ranges. The 60% confidence interval ranges of the biobased product production costs are 0.64–1.10 US$ kg−1 ethanol, 1.18–2.05 US$ kg−1 ethylene, 1.37–2.40 US$ kg−1 1,3‐PDO, and 1.91–2.57 US$ kg−1 succinic acid. The cost ranges of all biobased products partly or completely overlap with the ranges of the production costs of the fossil equivalent products. The results show that sugarcane‐based 1,3‐PDO and to a lesser extent succinic acid have the highest potential benefit. The ranges of GHG emission reduction are 1.29–2.16, 3.37–4.12, 2.54–5.91, and 0.47–5.22 CO2eq kg−1 biobased product for ethanol, ethylene, 1,3‐PDO, and succinic acid respectively. Considering the potential GHG emission reduction and profit per hectare, the pathways using sugarcane score are generally better than eucalyptus feedstock due to the high yield of sugarcane in Brazil. Overall, it was not possible to choose a clear winner, (a) because the best performing biobased product strongly depends on the chosen metric, and (b) because of the large ranges found, especially for PDO and succinic acid, independent of the chosen metric. To quantify the performance better, more data are required regarding the biobased product yield, equipment costs, and energy consumption of biobased industrial pathways, but also about the production costs and GHG emission intensity of fossil‐equivalent products. © 2019 The Authors. Biofuels, Bioproducts, and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...