Analysis of Greenhouse Gas Emissions in Centralized and Decentralized Water Reclamation with Resource Recovery Strategies in Leh Town, Ladakh, India, and Potential for Their Reduction in Context of the Water–Energy–Food Nexus

Comprehensive analysis of greenhouse gas emissions and emission factors in a Korean domestic wastewater treatment plant: Insights into mechanisms and pathways for climate change mitigation

Carbon footprint of a conventional wastewater treatment plant: An analysis of water-energy nexus from life cycle perspective for emission reduction

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions.

At present, urban greenhouse gas (GHG) emissions from different wastewater treatment stages are attracting increasing attention. Based on the Guidelines of the China Greenhouse Gas List Compilation (Trial) and the IPCC National Greenhouse Gas List Guidelines in 2006, this paper evaluated urban GHG emissions from wastewater treatment in China from 2011 to 2020. The contribution rates of GHG emissions to the total GHG emissions were calculated for the different wastewater treatment stages. The variations in annual GHG emissions and differences in GHG emissions among different regions and provinces were also analyzed. The total amount of equivalent CO2 emissions reaches 1478.51 million tons, and the annual average amount of equivalent CO2 emissions from 2011 to 2020 is 147.9 million tons, which shows a trend of decreasing first and then increasing. The distribution of GHG emissions from wastewater treatment is uneven among provinces and regions; Guangdong Province has the highest emission, while the Xizang autonomous Region has the lowest. The correlation and contribution rate analysis revealed that paper production and chemical and side food production could discharge a large amount of wastewater with a high COD content, which may have an important impact on GHG emissions during the wastewater treatment stages. According to the study results, CH4 accounts for the largest proportion (63.08%) of the total GHG emissions. The most important source of CH4 comes from the industrial wastewater treatment stage. The annual average CO2 emissions account for 22.24% of the total GHG emissions, which are mainly from the power and chemical consumption stage. The annual average N2O emissions account for 14.68% of the total GHG emissions and are mainly from the wastewater collection and discharge stage. Therefore, in the future, GHG emission reduction strategies should focus on CH4 emissions in the industrial wastewater treatment stage and develop CH4 recycling and utilization technologies.

This article discusses the challenges of adapting to and mitigating climate change through sustainable resource management in the agri-food sector. These aspects are mandatory obligations for businesses under new EU directives and regulations. Greenhouse gas (GHG) emissions must be controlled at every stage of the value chain, from the acquisition of raw materials to transportation and cooperation with suppliers. The purpose of this paper is to analyze the areas generating GHG emissions in the agri-food enterprise toward the development of guidelines for the sustainable development of domestic food production. This paper presents a GHG study in three scopes at one of the mills in Poland based on the GHG protocol methodology. The analysis of consumption of energy carriers was used to determine GHG emissions (Scopes 1 and 2), and the total amounted to about 2.1 million kg CO2eq (the share of Scope 1 was about 16% and Scope 2 as high as 83%), and the average carbon footprint of flour production in terms of unit weight was 0.040 kg CO2eq/kg. Extending the analysis to Scope 3, the emissions associated with this scope accounted for the largest share (92%), while Scopes 1 and 2 accounted for only 8%. The determined carbon footprint (considering the three GHG emission scopes) was 0.52 kg CO2eq/kg. In Scope 3, the largest contribution was from category 1 emissions (92%) related to grain cultivation, and category 5 (6%) were emissions related to the transportation of sold products. The smallest impact is from category 3 emissions related to the management of generated waste. Regular calculation and reporting of emissions in each area enables the company to more fully understand its environmental impact, identify risks and implement changes that bring financial and environmental benefits.

Statistical analysis of greenhouse gas emissions of South Korean residential buildings

Household activities such as the use of electricity, LPG, and fuel for vehicles are sources of greenhouse gas emissions. Energy consumption at the household scale continues to increase, especially during the COVID-19 pandemic due to the policy of working from home. The global COVID-19 pandemic also affects household-scale energy consumption for urban and suburban areas. The increase in energy consumption is in line with the increase in greenhouse gases so to reduce greenhouse gas emissions, spatial mapping is necessary. This mapping aims to determine the potential distribution of greenhouse gas emissions from household-scale LPG consumption so that programs, plans, or policies can be determined in strategies for reducing greenhouse gas emissions. The stages of this research begin with calculating GHG emissions using the IPPC method and making a GHG potential map. The research results from the calculation of greenhouse gas emissions in the household-scale LPG sector in the study area ranged from 110 – 2792 tons CO2eq/year. GHG emissions in sub-urban areas are greater than in urban areas because they are influenced by population, LPG usage patterns, and income per capita.

Tropical reservoirs serve a crucial role in the efficient management of water resources contributing to public supply, irrigation, and flow regulation. However, they often emerge as significant sources of greenhouse gas (GHG) emissions and social conflicts. These aquatic ecosystems are located in various Brazilian biomes, such as the Belo Monte Hydroelectric Plant (UHE), situated in the Amazon biome, and the Pedreira and Duas Pontes reservoirs, currently under construction in the Atlantic Forest biome. Each of these reservoirs reflects the complexity of interactions between environmental and social factors, requiring meticulous analysis in light of growing concerns about climate change.The proposed research includes the collection and analysis of environmental and operational data related to these reservoirs, considering crucial variables such as flooded area, types of aquatic vegetation present, and local climatic data. A central focus of the study is to understand how social practices and land use in adjacent areas influence greenhouse gas (GHG) emissions. To achieve this, a comprehensive analysis of agricultural and urban activities that may affect both the availability of organic matter and the decomposition dynamics in the reservoirs is conducted.The methodology adopted utilizes a socio-hydrological approach, allowing for an in-depth investigation of the interrelationships between social and environmental factors. The research includes the application of the G-Res tool to calculate the greenhouse gas (GHG) emissions resulting from management practices in the reservoirs. The aim is to understand the community's perceptions regarding water, conservation practices, and their correlations with GHG emissions, with the goal of providing practical recommendations that promote more efficient and sustainable water management.The study aims to develop future solutions that address interconnected environmental and social issues, aligning with the goals of water sustainability in Brazil, minimizing GHG emissions, and encouraging sustainable practices; thereby contributing to the conservation of water resources and improving the quality of life for local communities. Keywords: Tropical Reservoirs, Greenhouse Gases, Sustainable Water Management, Socio-Hydrological Approach, Tropical Biomes.

The Australian dairy industry contributes ~1.6% of the nation’s greenhouse gas (GHG) emissions, emitting an estimated 9.3 million tonnes of carbon dioxide equivalents (CO2e) per annum. This study examined 41 contrasting Australian dairy farms for their GHG emissions using the Dairy Greenhouse Gas Abatement Strategies calculator, which incorporates Intergovernmental Panel on Climate Change and Australian inventory methodologies, algorithms and emission factors. Sources of GHG emissions included were pre-farm embedded emissions associated with key farm inputs (i.e. grains and concentrates, forages and fertilisers), CO2 emissions from electricity and fuel consumption, methane emissions from enteric fermentation and animal waste management, and nitrous oxide emissions from animal waste management and nitrogen fertilisers. The estimated mean (±s.d.) GHG emissions intensity was 1.04 ± 0.17 kg CO2 equivalents/kg of fat and protein-corrected milk (kg CO2e/kg FPCM). Enteric methane emissions were found to be approximately half of total farm emissions. Linear regression analysis showed that 95% of the variation in total farm GHG emissions could be explained by annual milk production. While the results of this study suggest that milk production alone could be a suitable surrogate for estimating GHG emissions for national inventory purposes, the GHG emissions intensity of milk production, on an individual farm basis, was shown to vary by over 100% (0.76–1.68 kg CO2e/kg FPCM). It is clear that using a single emissions factor, such as milk production alone, to estimate any given individual farm’s GHG emissions, has the potential to either substantially under- or overestimate individual farms’ GHG emissions.

Life cycle analysis of greenhouse gas emissions from organic and conventional food production systems, with and without bio-energy options

In recent years, the issue of climate change has gained significant attention and become a focal point of discussion in various sectors of civil society. Governments, individuals, and scientists worldwide are increasingly concerned about the observed changes in climate patterns, often attributed to the rising levels of greenhouse gases. In this context, the main objective of this study is to assess the greenhouse gas emissions associated with the railway system in the state of Pernambuco, Brazil, and compare them with other national case studies, aiming to obtain greenhouse gas emission parameters specific to the railway system and propose mitigation models to address this environmental impact in the air. To achieve this goal, a comprehensive life cycle assessment (LCA) methodology was employed to examine the life cycle of the Pernambuco Metro. This involved conducting an inventory of resource inputs and emissions using actual observed data. Additionally, a comparative analysis of greenhouse gas emissions across different urban rail transport systems is presented to provide valuable contextual insights. The study findings reveal that the total greenhouse gas emissions from the Pernambuco rail system amount to 6170.54 t CO2e. Considering a projected total service life of 50 years, the estimated greenhouse gas emissions for the entire life cycle of the system’s operation and maintenance reach 308,550 t CO2e. The interdisciplinary nature of this research highlights the significance of studying the atmospheric effects of the Pernambuco railway system as a crucial parameter for designing strategies and technologies aimed at reducing air pollution within the region. Through quantifying and analyzing the greenhouse gas emissions of the Pernambuco rail system, this study provides valuable insights that contribute to addressing concerns related to climate change and promoting sustainable practices. It underscores the importance of developing effective strategies to mitigate air pollution and facilitates informed decision-making for the future of urban transportation systems.

As the transportation sector is one of the main emitters of large quantities of pollutions to the atmosphere, industries have been trying to cope with this issue and launch many campaigns or projects to reduce air pollutions. In any industries around the world, an electric vehicle is a part of alternative transportation mode which has recently experienced considerable growth. The paper aims to evaluate energy consumption and greenhouse gas (GHG) emissions of the food sector for the entire life cycle and particularly focusing on green road transportation. The focus of the analysis covers the mango powder drink mix transportation, distribution, and disposal aspects, especially for road transportation. The observed results showed that the electric vehicles have emissions reduction potential and consequently showed low impacts in Global Warming Potential (GWP) impact category. The environmental impact assessment identified that the primary source of energy use and GHG emissions was the transportation process from Hong Keaw plantation to King Mongkut’s Institute of Technology Ladkrabang (KMITL) (0.025 kgCO2eq).

Objectives:In accordance with the concern of global warming problem, many companies in Korea are striving to reduce greenhouse gas emissions in accordance with consumer awareness. Many studies have been reported for various products; however it is difficult to find carbonated soft drinks in Korea. The purpose of this study is to the impact of the greenhouse gas emissions, especially carbonated soft drinks in Korea.Methods:Calculation method of the greenhouse gas emissions followed “Guidelines for Carbon Footprint of Products” used in Korean Carbon Footprint Labeling. It was developed based on international standards such as ISO 14040 series. Life cycle of carbonated soft drinks was considered as a pre-manufacturing stage, manufacturing stage, distribution and disposal stage. Use stage of the product was excluded.Results and Discussion:This study shows that the package types and amounts for pre-manufacturing, manufacturing and disposal steps of carbonated soft drinks (the unit contents: 500 mL/unit, 1.5 L/unit), and also shows the results of greenhouse gas emissions. From the results, the pre-manufacturing stage of PET bottle manufacturing is the first contributor that occupy above 60% of greenhouse gas emissions. For reducing carbon emissions, low carbon manufacturing techniques for PET bottle are important. Sensitivity analysis was performed for PET bottle manufacturing, cap manufacturing and waste plastic disposal including site data and assumptions made. The sensitivity of each item was less than 7%.Conclusions:In conclusion, this study shows that the pre-manufacturing step of PET bottle and cap production have very significant impact on the greenhouse gas emissions. Therefore lightweight packages and usage of recycled plastics would be main techniques for reducing greenhouse gas emissions of carbonated soft drinks. From this study, the increment of product’s carbon footprint certification would be used as an effective policy instrument for achieving reduction goals of Korea Government. And also it could be used to spread the culture of reducing greenhouse gas emissions.

<div class="section abstract"><div class="htmlview paragraph">The depletion of fossil fuels and the emergence of global warming propel public sectors to explore alternative energy such as renewable electricity and hydrogen to reduce greenhouse gas (GHG) emissions. Numerous studies have demonstrated substantial environmental benefits of electric light-duty vehicles. However, research focusing on heavy-duty vehicles is still relatively scarce, and the transition to zero emissions heavy-duty trucks is facing enormous technical and economic challenges. This work investigated GHG emissions during the manufacturing and assembly phase of heavy-duty vehicles (HDVs), including battery electric trucks (BETs) and gaseous hydrogen fuel cell electric trucks (FCETs) using SimaPro software package with wildly accepted Ecoinvent database based on UK grid mix scenarios. A comparative analysis of greenhouse gas (GHG) emissions during the production phase of 700 bar- and 350 bar-H<sub>2</sub> FCETs and their battery electric counterparts (eqBETs) was conducted under two UK electricity grid mix scenarios: current and 2050 future electricity grid mixes. The baseline vehicles are 19500 kg H<sub>2</sub> fuel cell electric rigid truck (350 bar H<sub>2</sub>) and 37195 kg H<sub>2</sub> fuel cell electric articulated truck (700 bar H<sub>2</sub>). In the context of the current UK grid mix, the results indicated that the production of the 19.5 tons 350 bar-H<sub>2</sub> FCET accounted for unit emissions (per ton of vehicle weight) of 4306.09 kg CO<sub>2_eq</sub>/t, while 700 bar-H<sub>2</sub> FCET (37.195 tons) had emissions of 3868.17 kg CO<sub>2_eq</sub>/t. By contrast, the 700 bar-eqBET exhibited unit GHG emissions of 7314.98 kg CO<sub>2_eq</sub>/t, while 350 bar-eqBET showed slightly higher emissions of 7396.06 kg CO<sub>2_eq</sub>/t. Additionally, the 700 bar-H<sub>2</sub> FCET demonstrated more promising performance in reducing production related GHG emissions compared to other truck scenarios under the future electricity grid mix.</div></div>