Water-energy-carbon nexus and de-carbonation pathways in integrated urban water system for a megacity study.

Assessment on embodied energy and greenhouse gas emissions in urban water system from life cycle perspective: A typical case of India

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.

Spatial heterogeneity of factors affecting GHG emission intensity in urban water supply and wastewater treatment systems in China

Hidden greenhouse gas emissions for water utilities in China's cities

This study presents a holistic approach to evaluate energy performance and greenhouse gas (GHG) emissions from urban water supply and sanitation stages, which are important for sustainable water management and climate change mitigation. The study was conducted for Antalya city of Turkey to compare baseline and improved scenario conditions using the Energy Performance and Carbon Emissions Assessment and Monitoring (ECAM) tool. The current application of urban water and wastewater services was defined as the baseline scenario. For the improved urban water cycle, the reduction of non-revenue water, onsite sanitation prevention, increase in energy efficiency, biogas production and reuse of treated wastewater were investigated. Water supply and sanitation stages contributed to approximately 26 and 74% of total GHG emissions and 70 and 30% of energy consumption for the baseline scenario, respectively. GHG emissions were determined approximately as 52,423 tCO2eq/year for CO2 (40%), 47,029 tCO2eq/year for CH4 (35%) and 33,006 tCO2eq/year for N2O (25%) for the baseline scenario. The total GHG emissions of 132,457 tCO2eq/year and energy consumption of 136,328 MWh/year were reduced by 27.65% for GHG emissions and 16.48% for energy consumption for the improved urban water cycle. The outcomes of this research are expected to achieve sustainable cities and combat climate change.

Researchers at Argonne National Laboratory expanded the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model and incorporated the fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). The WTW results were separately calculated for the blended charge-depleting (CD) and charge-sustaining (CS) modes of PHEV operation and then combined by using a weighting factor that represented the CD vehicle-miles-traveled (VMT) share. As indicated by PSAT simulations of the CD operation, grid electricity accounted for a share of the vehicle's total energy use, ranging from 6% for a PHEV 10 to 24% for a PHEV 40, based on CD VMT shares of 23% and 63%, respectively. In addition to the PHEV's fuel economy and type of on-board fuel, the marginal electricity generation mix used to charge the vehicle impacted the WTW results, especially GHG emissions. Three North American Electric Reliability Corporation regions (4, 6, and 13) were selected for this analysis, because they encompassed large metropolitan areas (Illinois, New York, and California, respectively) and provided a significant variation of marginal generation mixes. The WTW results were also reported for the U.S. generation mix and renewable electricity to examine cases of average and clean mixes, respectively. For an all-electric range (AER) between 10 mi and 40 mi, PHEVs that employed petroleum fuels (gasoline and diesel), a blend of 85% ethanol and 15% gasoline (E85), and hydrogen were shown to offer a 40-60%, 70-90%, and more than 90% reduction in petroleum energy use and a 30-60%, 40-80%, and 10-100% reduction in GHG emissions, respectively, relative to an internal combustion engine vehicle that used gasoline. The spread of WTW GHG emissions among the different fuel production technologies and grid generation mixes was wider than the spread of petroleum energy use, mainly due to the diverse fuel production technologies and feedstock sources for the fuels considered in this analysis. The PHEVs offered reductions in petroleum energy use as compared with regular hybrid electric vehicles (HEVs). More petroleum energy savings were realized as the AER increased, except when the marginal grid mix was dominated by oil-fired power generation. Similarly, more GHG emissions reductions were realized at higher AERs, except when the marginal grid generation mix was dominated by oil or coal. Electricity from renewable sources realized the largest reductions in petroleum energy use and GHG emissions for all PHEVs as the AER increased. The PHEVs that employ biomass-based fuels (e.g., biomass-E85 and -hydrogen) may not realize GHG emissions benefits over regular HEVs if the marginal generation mix is dominated by fossil sources. Uncertainties are associated with the adopted PHEV fuel consumption and marginal generation mix simulation results, which impact the WTW results and require further research. More disaggregate marginal generation data within control areas (where the actual dispatching occurs) and an improved dispatch modeling are needed to accurately assess the impact of PHEV electrification. The market penetration of the PHEVs, their total electric load, and their role as complements rather than replacements of regular HEVs are also uncertain. The effects of the number of daily charges, the time of charging, and the charging capacity have not been evaluated in this study. A more robust analysis of the VMT share of the CD operation is also needed.

Researchers at Argonne National Laboratory expanded the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model and incorporated the fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). The WTW results were separately calculated for the blended charge-depleting (CD) and charge-sustaining (CS) modes of PHEV operation and then combined by using a weighting factor that represented the CD vehicle-miles-traveled (VMT) share. As indicated by PSAT simulations of the CD operation, grid electricity accounted for a share of the vehicle's total energy use, ranging from 6% for a PHEV 10 to 24% for a PHEV 40, based on CD VMT shares of 23% and 63%, respectively. In addition to the PHEV's fuel economy and type of on-board fuel, the marginal electricity generation mix used to charge the vehicle impacted the WTW results, especially GHG emissions. Three North American Electric Reliability Corporation regions (4, 6, and 13) were selected for this analysis, because they encompassed large metropolitan areas (Illinois, New York, and California, respectively) and provided a significant variation of marginal generation mixes. The WTW results were also reported for the U.S. generation mix and renewable electricity to examine cases of average and clean mixes, respectively. For an all-electric range (AER) between 10 mi and 40 mi, PHEVs that employed petroleum fuels (gasoline and diesel), a blend of 85% ethanol and 15% gasoline (E85), and hydrogen were shown to offer a 40-60%, 70-90%, and more than 90% reduction in petroleum energy use and a 30-60%, 40-80%, and 10-100% reduction in GHG emissions, respectively, relative to an internal combustion engine vehicle that used gasoline. The spread of WTW GHG emissions among the different fuel production technologies and grid generation mixes was wider than the spread of petroleum energy use, mainly due to the diverse fuel production technologies and feedstock sources for the fuels considered in this analysis. The PHEVs offered reductions in petroleum energy use as compared with regular hybrid electric vehicles (HEVs). More petroleum energy savings were realized as the AER increased, except when the marginal grid mix was dominated by oil-fired power generation. Similarly, more GHG emissions reductions were realized at higher AERs, except when the marginal grid generation mix was dominated by oil or coal. Electricity from renewable sources realized the largest reductions in petroleum energy use and GHG emissions for all PHEVs as the AER increased. The PHEVs that employ biomass-based fuels (e.g., biomass-E85 and -hydrogen) may not realize GHG emissions benefits over regular HEVs if the marginal generation mix is dominated by fossil sources. Uncertainties are associated with the adopted PHEV fuel consumption and marginal generation mix simulation results, which impact the WTW results and require further research. More disaggregate marginal generation data within control areas (where the actual dispatching occurs) and an improved dispatch modeling are needed to accurately assess the impact of PHEV electrification. The market penetration of the PHEVs, their total electric load, and their role as complements rather than replacements of regular HEVs are also uncertain. The effects of the number of daily charges, the time of charging, and the charging capacity have not been evaluated in this study. A more robust analysis of the VMT share of the CD operation is also needed.

There are two types of approaches for analyzing various aspects related to green-house gas (GHG) emissions, i.e., top-down and bottom-up approaches. Although the top-down approach focuses on macro-economic perspectives, the bottom-up approach is more suitable to investigate GHG emissions at an industry level utilizing domain-specific knowledge. For example, a bottom-up analysis requires a wide variety of data such as energy demands, conversion factors, and energy efficiency, which may be obtained by analyzing industrial process data. This study aims to provide a bottom-up approach for analyzing GHG emissions from shipbuilding processes in Korea. Reference energy system and energy balance for shipbuilding processes are derived for bottom-up modeling. Based on the midterm forecast on energy demands of the Korean shipbuilding industry, it is shown that the business-as-usual GHG emissions may be obtained. Relevant mitigation measures are then investigated to analyze their mitigation potentials for low-carbon ship production. 1. Introduction Global climate change has recently drawn an increasing attention due to its adverse effects on our environment. Since the inception of Kyoto Protocol to the United Nations Frame-work conventions on climate change, local and international experts have long called for more international cooperation in coping with global warming. The main idea of international cooperative efforts is to impose binding obligations for greenhouse gas (GHG) emissions on participating countries. Even though some countries have withdrawn their commitment and others have been reluctant to adopting definite targets for emission reduction, many countries have already established a designated national authority to manage their GHG emissions. Korea has also established a national authority called "GHG Inventory and Research Center (GIR)" in 2010. One of the most important roles of GIR is to manage the national GHG emission levels and set the abatement target of various sectors through an efficient and integrated management of GHG-related information. Recently, GIR has conducted a series of research projects to analyze GHG emissions of industrial sectors in cooperation with a group of experts. This study presents the results from the analysis of GHG emissions and mitigation potentials for the shipbuilding processes in Korea. It should be noted that the scope of this study is limited to constructions processes in a shipyard even though the shipbuilding industry may encompass a broader range of industrial sectors such as steel production and transport. Adopting Model for Energy Supply Strategy Alternatives and their General Environmental Impacts (MESSAGE) developed by International Institute for Applied Systems Analysis in 1980s (Messner 1997), a bottom-up mathematical programming model is generated to derive the business-as-usual (BAU) GHG emissions in the construction processes in a shipyard. Abatement potentials of several technical abatement measures are also analyzed to help shipbuilders effectively cope with the issue of climate change.

The intensive use of antibiotics for medical, veterinary, or agricultural purposes results in the continuous release of antibiotics into the environment, leading to the increasingly widespread occurrence of antibiotic resistance. Although antibiotic resistance has been recognized as a major threat to human health worldwide, the related phenomenon occurring in natural and engineered environments has so far been largely overlooked. The urban (including industrial) water cycle, which connects urban life, agriculture, and the environment, is potentially a hot spot for the spread of antibiotic resistance. Therefore, better understanding of the distribution and transportation of antibiotic-resistant bacteria (ARB) and acquisition of antibiotic resistance genes (ARGs) in the urban water cycle is critically important to improve the control of this emerging environmental and human health challenge. In this book chapter, we comprehensively review the occurrence, transfer, and acquisition mechanisms of ARGs in the urban water cycle. Various methods that are used to monitor ARB and ARGs are compared in terms of their strengths and limitations. Opportunities for the development of real-time monitoring methods are discussed, along with possible control strategies for ARB and ARGs in urban water environments. We recommend that three major barriers should be developed to minimize or halt the spread of ARGs in urban water systems, including more efficient water disinfection, advanced wastewater treatment, and optimized sludge treatment processes.

This study evaluated greenhouse gas (GHG) emissions from an urban water system in Taiwan using a lifecycle assessment method. The water system of the Taipei region was used as a case study. Both on‐site and off‐site emissions of GHGs were considered. Total GHG emissions from the urban water system were 151,211.3 t CO2‐eq/y in the study period. On‐site GHG emissions from water surfaces and chemical additives contributed 3.1% and 18.3% of total emissions. The reservoir accounted for 1% of total off‐site GHG emissions from electricity consumption; 60.3% was from purification plants and 38.7% from boosting stations. The environmental cost of GHG emissions from the urban water system was calculated as US$0.001 per ton of water, which implies that the water price in Taiwan should be increased to US$0.27/t. This study explored the principle of ‘user pays’ in water pricing by monetizing the environmental cost of GHG emissions.

The energy consumption and greenhouse gas (GHG) emissions associated with urban water systems have come under scrutiny in recent times, as a result of increasing interest in climate change, to which urban water systems are particularly vulnerable. The approach most commonly taken previously to modelling these results has been to consider various urban water system components in great detail, but in isolation from the rest of the system. This piecewise approach is suboptimal, since it systematically fails to reveal the relative importance of the energy consumption and GHG emissions associated with each system component in the context of the entire urban water system. Hence, it was determined that a new approach to modelling the energy consumption and GHG emissions associated with urban water systems was necessary. It was further determined that the value derived from such a model would be greatly enhanced if it could also model the water consumption and wastewater generation associated with each system component, such that integrated policies could be developed, aimed at minimising water consumption, wastewater generation, energy consumption and GHG emissions concurrently. Hence, the following research question was posed: How should the relationships between the water consumption, wastewater generation, energy consumption and GHG emissions associated with the operation of urban water systems be modelled such that the impact of various changes to the system configuration made at different spatial scales can be determined within the context of the entire system? In this research project, life cycle assessment ideas were employed to develop such a new modelling methodology. Initially, the approach was developed at the building-scale, such that the end uses of water present in a selected building and any associated appliances could be modelled, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that building. This vast breadth of scope was delivered by considering only the operational life cycle stage of each urban water system component, excluding both the pre- and post-operational life cycle stages of the associated infrastructure. The value of this pilot model was illustrated by several case studies, focused on residential buildings connected to the centralised water supply and wastewater systems in Melbourne, Australia. Later, the approach was extended to the city-scale by using probabilistic distributions of each input parameter, such that all of the end uses of water present in a city, and all of the associated building-scale appliances could be modelled, along with the associated complete water supply and wastewater systems. The value of this city-scale model was illustrated by applying it to model a hypothetical case study city, resembling Melbourne, Australia in many ways. Due to a lack of data, this application was limited to the residential sector of the case study city, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that sector. The results generated by the pilot and city-scale models showed that the new modelling methodology could be employed at a wide range of scales to assess the relative importance of each modelled urban water system component in terms of the specified results. Importantly, the high resolution of those results enabled the identification of the underlying causes of the relative importance of each urban water system component, such that efficient and effective approaches to reducing each result for each system component could be developed. Interestingly, for the specific case studies investigated, it was revealed that some commonly neglected system components were actually extremely important, such as domestic hot water services, a trend found to be largely driven by hot water consumption in showers.

Urban water management policy in Japan, with examples from Fukuoka city, is described and the potential for sustainability of Fukuoka's urban water system is discussed. A framework of the qualitative characteristics of a sustainable system (including social, environmental and economic factors) is developed and used in the analyses presented here. The Fukuoka example shows that technically advanced solutions for use of reclaimed water and rainwater in buildings can be practically and economically feasible. Regarding the organization it is shown that the wastewater sector has a somewhat lower status than the water sector. It is argued that merging the water and wastewater sectors could stimulate the development of a holistic approach to urban water management, contribute to increasing resources availability for the wastewater sector and, in this way, the overall sustainability of the urban water system. Tackling water shortages through controlling water demand, investments in increasing water distribution efficiency and utilization of reclaimed water and rainwater in Fukuoka are all in line with increasing sustainability of the urban water system.

Toward carbon mitigation resiliency in the agriculture sector: An integrated LCA-GHG protocol-IPCC guidelines framework for biofertilizer application in paddy field.

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.

Comprehensive analysis of greenhouse gases emissions and microbial dynamics in glacier-fed lakes across various ablation stages.