Energy use and recovery in waste management and implications for accounting of greenhouse gases and global warming contributions

Low-carbon competitiveness of cities in solid waste disposal systems: Spatial and temporal variations in greenhouse gas emissions in the Yangtze River Delta.

PurposeVariability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.MethodsData from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.Results and discussionBoth inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5 × 102 g CO2−eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.ConclusionsThe combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

Intensive cultivation and post-harvest vegetable oil production stages are major sources of greenhouse gas (GHG) emissions. Variation between production systems and reporting disparity have resulted in discordance in previous emissions estimates. The aim of this study was to assess global systems-wide variation in GHG emissions resulting from palm, soybean, rapeseed and sunflower oil production. Such an analysis is critical to understand the implications of meeting increasing edible oil demand. To achieve this, we performed a unified re-analysis of life cycle input data from diverse palm, soybean, rapeseed, and sunflower oil production systems, from a saturating search of published literature. The resulting dataset reflects almost 6000 producers in 38 countries, and is representative of over 71% of global vegetable oil production. Across all oil crop systems, median GHG emissions were 3.81 kg CO2e per kg refined oil. Crop specific median emissions ranged from 2.49 kg CO2e for rapeseed oil to 4.25 kg CO2e for soybean oil per kg refined oil. Determination of the carbon cost of agricultural land occupation revealed that carbon storage potential in native compared to agricultural land cover drives variation in production GHG emissions, and indicates that expansion of production in low carbon storage potential land, whilst reforesting areas of high carbon storage potential, could reduce net GHG emissions whilst boosting productivity. Nevertheless, there remains considerable scope to improve sustainability within current production systems, including through increasing yields whilst limiting application of inputs with high carbon footprints, and in the case of palm oil through more widespread adoption of methane capture technologies in processing stages.

Analyzing the variation of greenhouse gas emissions from typical municipal wastewater treatment plants in Beijing during 2007–2021

Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

A dominance analysis of greenhouse gas emissions, beef output and land use of German dairy farms

Greenhouse gas (GHG) emissions emanating from waste management practices in five Norwegian military camps were assessed. The GHG emission accounting practices examined included fuel provision upstream of a material recovery facility (MRF), operational activities at the MRF, and downstream processes. The latter means recycling of waste compared to primary production using virgin materials, or the incineration of waste with energy recovery compared to heating based on the average energy mix for both EU and Norway. The results show that the operational activities at the MRF cause more GHG emissions than the provision of fuel upstream of the MRF (116 vs. 16-21 tonnes CO2-eq., respectively). Furthermore, the downstream activities provided far greater avoidance of GHG emissions than the load caused by upstream activities and the activities at the MRF. Recycling proves to be beneficial over incineration of waste when compared to the EU energy mix (savings of--257 tonnes CO2-eq.), and the advantage is even larger when compared to the average energy mix for Norway (savings of--779 tonnes CO2-eq.). In conclusion, the results show that sorting of mixed waste at military camp collection sites followed by recycling of the separated fractions at MRF would result in significant avoidance of GHG emissions, compared to the current practice of incineration with energy recovery of the mixed waste.

This paper highlights the importance of precise assessments of greenhouse gas (GHG) emissions associated with power generation for effective policy making in environmental sustainability. The current assessment approaches based on historical data or estimated generation using energy models may not accurately reflect the reality of future power systems due to the impact of spatial-temporal and techno-economic characteristics of generation mix and load demands. To address this, the paper presents a comprehensive methodology for accurately quantifying the geographical and temporal variations in GHG emissions associated with generating units’ operation, startup, and shutdown at an hourly resolution. The methodology is based on a detailed electricity model that considers various sources of generation, techno-economic, and spatial-temporal characteristics of system components. The study demonstrates the effectiveness of the methodology in quantifying GHG emissions in the IEEE RTS-GLMC system, with a focus on CO2, N2O, and CH4. The analysis reveals significant variations in GHG emissions among different generation buses and hours of the year, attributed to the high proportion of renewable energy in the generation mix. The paper emphasizes the inadequacy of examining marginal environmental impacts based on GHG emission intensity alone and suggests a more thorough analysis based on total GHG emissions generation. Finally, the paper emphasizes the crucial role of time-varying and marginal assessment techniques in identifying effective strategies for reducing GHG emissions in the electricity sector, including optimizing the operation and capacity of generation units, energy storage systems, and electric vehicles, including their locations.

Political governance, socioeconomics, and weather influence provincial GHG emissions in Canada

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Assessment of GHG Emissions and Their Variability of Meat Production Systems in Wallonia Based on Grass and Maize

Small thermokarst lakes, formed by the thawing of ice-rich permafrost, can emit significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. The physical processes behind diurnal variations in greenhouse gas (GHG) emissions from thermokarst lakes remain poorly understood due to a lack of observational data in subarctic regions. This study focuses on the dynamics of GHG emissions from two small lakes (< 200 m2) located in the Tasiapik Valley, near the village of Umiujaq, Nunavik, Canada (56°33'28.8"N 76°28'46.5"W). One lake is characterized by a more humic and sheltered environment, while the other is characterized by greater transparency and exposure to wind. Continuous measurements of temperature, conductivity, and oxygen in the water column, as well as meteorological conditions (wind, pressure, heat exchanges) have been conducted since October 2021. CO2 fluxes measured using a floating chamber and dissolved gases (CO2, CH4, N2O) at the surface were measured on a daily cycle for 2-week periods in July 2022 and August 2023, with bubble traps quantifying ebullition rates. Diffusive CO2 fluxes are in line with estimates for other thermokarst lakes, ranging from –2 to 17 mmol m–2 d–1 in July 2022 (during a particularly cold period) and from 8 to 66 mmol m–2 d–1 in August 2023, a period of stronger stratification. Turbulence, characterized by the gas transfer coefficient k600, was higher in 2023 (0.4 to 10.4 cm h–1) than in 2022 (1.1 to 4.7 cm h–1). CH4 emission through ebullition was more than 6 times higher than through diffusion in the more humic and sheltered lake (13 ± 5.5 mol m–2 d–1) and almost 7 times higher than in the more transparent and exposed lake (2 ± 1.5 mmol m–2 d–1), where ebullition was of the same order of magnitude than diffusion. Diurnal cycles were characterized by the nocturnal mixing of surface waters with deeper waters enriched in CO2, leading to a peak in CO2 fluxes in the morning, which gradually decreased over the course of the day with the establishment of thermal stratification due to solar radiation, and the potential uptake by primary production. Overall, these results highlight the complex interactions between environmental factors influencing GHG emissions in thermokarst lakes, and the major differences that can exist between adjacent lakes.

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 ...

Current and future greenhouse gas (GHG) emissions from the management of municipal solid waste in the eThekwini Municipality – South Africa

Addressing dairy industry's scope 3 greenhouse gas emissions by efficiently managing farm carbon footprints