Estimation of greenhouse gas emissions from an underground wastewater treatment plant

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system. The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis. The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 104 t CO2eq year−1, 64.9%) is the most significant for total GHG emissions (5.65 × 104 t CO2eq year−1) because a huge amount of CH4 (3.51 × 104 t CO2eq year−1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH4 emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions. This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

Despite the ever-growing body of life cycle assessment (LCA) literature on electricity generation technologies, inconsistent methods and assumptions hamper comparison across studies and pooling of published results. Synthesis of the body of previous research is necessary to generate robust results to assess and compare environmental performance of different energy technologies for the benefit of policy makers, managers, investors, and citizens. With funding from the U.S. Department of Energy, the National Renewable Energy Laboratory initiated the LCA Harmonization Project in an effort to rigorously leverage the numerous individual studies to develop collective insights. The goals of this project were to: (1) understand the range of published results of LCAs of electricity generation technologies, (2) reduce the variability in published results that stem from inconsistent methods and assumptions, and (3) clarify the central tendency of published estimates to make the collective results of LCAs available to decision makers in the near term. The LCA Harmonization Project's initial focus was evaluating life cycle greenhouse gas (GHG) emissions from electricity generation technologies. Six articles from this first phase of the project are presented in a special supplemental issue of the Journal of Industrial Ecology on Meta-Analysis of LCA: coal (Whitaker et al. 2012), concentratingmore » solar power (Burkhardt et al. 2012), crystalline silicon photovoltaics (PVs) (Hsu et al. 2012), thin-film PVs (Kim et al. 2012), nuclear (Warner and Heath 2012), and wind (Dolan and Heath 2012). Harmonization is a meta-analytical approach that addresses inconsistency in methods and assumptions of previously published life cycle impact estimates. It has been applied in a rigorous manner to estimates of life cycle GHG emissions from many categories of electricity generation technologies in articles that appear in this special supplemental supplemental issue, reducing the variability and clarifying the central tendency of those estimates in ways useful for decision makers and analysts. Each article took a slightly different approach, demonstrating the flexibility of the harmonization approach. Each article also discusses limitations of the current research, and the state of knowledge and of harmonization, pointing toward a path of extending and improving the meta-analysis of LCAs.« less

Estimation of greenhouse gas emissions from a hybrid wastewater treatment plant

Wastewater treatment plants (WWTPs) using membrane bioreactor (MBR) technology have been considered a significant source of greenhouse gas (GHG) emissions. This study chose a small-scale wastewater treatment plant using MBR technology to estimate its potential for GHG emissions. The total GHG emissions from this wastewater treatment plant ranged from 2,802 to 11,946kg CO2 -eq/month within the 4-year study period, and they were mainly attributable to electricity consumption (79.94%) followed by chemical usages (17.13%) and on-site GHG emissions (2.93%). The on-site GHG emissions varied monthly, but most of them ranged from 80 to 160kg CO2 -eq/month. The aeration tank was an important operating unit for GHG emissions. Off-site GHG emissions mainly came from carbon dioxide (CO2 ) emissions resulting from electricity consumption. The results of this study provide useful information about the potential of GHG emissions from WWTPs using MBR technology and indicate that WWTPs can be sustainably managed. PRACTITIONER POINTS: Wastewater treatment plants have been considered a source of greenhouse gas emissions. Total greenhouse gas emissions from the wastewater treatment plants using membrane bioreactor were mainly attributable to electricity consumption. On-site greenhouse gas emissions were relatively insignificant in this study.

Understanding the greenhouse gas emissions from China’s wastewater treatment plants: Based on life cycle assessment coupled with statistical data

Urban wastewater treatment plants are considered important greenhouse gas resources with massive emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) during operation. Based on the emission factor approach of pollutant reduction, the 2014 emission inventory of greenhouse gases (CO2, CH4, and N2O) from urban wastewater treatment plants in China was established. In addition, the temporal and spatial distribution and influencing factors of greenhouse gas emissions were analyzed in this study. The results showed that total emissions of greenhouse gas from urban wastewater treatment plants in China was 7348.60 Gg (CO2-eq) in 2014, which included CO2, CH4, and N2O emissions of 6054.57 Gg, 27.47 Gg (769.08 Gg, CO2-eq), and 1.98 Gg (524.95 Gg, CO2-eq), respectively. The difference in greenhouse gas emissions among provinces was significant:high emissions appeared in the eastern areas of China, low emissions were observed in the northwest, and hardly any emissions were found in Xizang. From 2005 to 2014, annual greenhouse gas emissions from urban sewage treatment plants in China increased by 229.4%, and the rates of CO2, CH4, and N2O increased by 217.9%, 217.9%, and 520.3%, respectively. The regional economic development level and number of wastewater treatment plants were correlated the most with the emissions of greenhouse gasses, and the per-capita protein supply was closely related with the N2O emission.

The estimation of greenhouse gas ( GHG ) emissions from a change in land‐use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel‐induced global land‐use change ( LUC ) GHG emissions. However, the science of LUC generally, and biofuels‐induced LUC specifically, is nascent and underpinned with great uncertainty. We critically review modeling approaches employed to estimate biofuel‐induced LUC and identify major challenges, important research gaps, and limitations of LUC studies for transportation fuels. We found LUC modeling philosophies and model structures and features (e.g. dynamic vs . static model) significantly differ among studies. Variations in estimated GHG emissions from biofuel‐induced LUC are also driven by differences in scenarios assessed, varying assumptions, inconsistent definitions (e.g. LUC ), subjective selection of reference scenarios against which (marginal) LUC is quantified, and disparities in data availability and quality. The lack of thorough sensitivity and uncertainty analysis hinders the evaluation of plausible ranges of estimates of GHG emissions from LUC . The relatively limited fuel coverage in the literature precludes a complete set of direct comparisons across alternative and conventional fuels sought by regulatory bodies and researchers. Improved modeling approaches, consistent definitions and classifications, availability of high‐resolution data on LUC over time, development of standardized reference and future scenarios, incorporation of non‐economic drivers of LUC , and more rigorous treatment of uncertainty can help improve LUC estimates in effectively achieving policy goals. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Abstract. Conferences, meetings and congresses are an important part of today's economic and scientific world. But the environmental impact, especially from greenhouse gas emissions associated with travel, can be extensive. Anthropogenic greenhouse gas (GHG) emissions account for the warming of the atmosphere and oceans. This study draws on the need to quantify and reduce greenhouse gas emissions associated with travel activities and aims to give suggestions for organizers and participants on possible ways to reduce greenhouse gas emissions, demonstrated on the example of the European Geography Association (EGEA) Annual Congress 2013 in Wasilkow, Poland. The lack of a comprehensive methodology for the estimation of greenhouse gas emissions from travel led to an outline of a methodology that uses geographic information systems (GIS) to calculate travel distances. The calculation of travel distances in GIS is adapted from actual transportation infrastructure, derived from the open-source platform OpenStreetMap. The methodology also aims to assess the possibilities to reduce GHG emissions by choosing different means of transportation and a more central conference location. The results of the participants of the EGEA congress, who shared their travel data for this study, show that the total travel distance adds up to 238 000 km, with average travel distance of 2429 km per participant. The travel activities of the participants in the study result in total GHG emissions of 39 300 kg CO2-eq including both outward and return trip. On average a participant caused GHG emissions of 401 kg CO2-eq. In addition, the analysis of the travel data showed differences in travel behaviour depending on the distance between conference site and point of origin. The findings on travel behaviour have then been used to give an estimation of total greenhouse gas emissions from travel for all participants of the conference, which result in a total amount of 79 711 kg CO2-eq. The potential for reducing greenhouse gas emissions by substituting short flights with train rides and car rides with bus and train rides is limited. Only 6 % of greenhouse gas emissions could be saved by applying these measures. Further considerable savings could only be made by substituting longer flights (32.6 %) or choosing a more central conference location (26.3 %).

Assessing the greenhouse gas mitigation potential of urban precincts with hybrid life cycle assessment

New Zealand has committed to a 50% reduction in greenhouse gas emissions (GHGEs) from 2005 levels by 2030. Dietary changes within New Zealand could simultaneously improve population health and contribute towards the nation’s emissions reduction target, as agricultural emissions are estimated to account for half of New Zealand’s GHGEs(1). This research aimed to quantify the GHGEs associated with household purchases of major food groups in New Zealand and identify the sociodemographic characteristics that are associated with per capita household dietary emissions. Household dietary emissions were estimated using the NielsenIQ Homescan(R) consumer panel — a large sample of households within New Zealand who report purchasing data of take-home food and beverages. The sample is nationally representative in terms of broad geographical regions and selected key demographic characteristics. Carbon emission estimates were assigned to 1,908,485 total food and beverage purchases from 1,775 households over one year (2019) using a process-based life cycle assessment (LCA) dataset initially constructed in the United Kingdom (UK) and adapted for New Zealand(2). This LCA dataset contains estimates of greenhouse gas emissions generated over the life cycle of the production of food products from the following stages: farming and processing, transit packaging, consumer packaging, transport, warehouse and distribution, refrigeration, and overheads. Greenhouse gas emissions are expressed in kg of carbon dioxide equivalents per kg of food product over a 100-year time horizon. Total emissions from purchases of major food groups were then estimated. Multiple linear regression was used to examine the relationships between household variables and per capita dietary emissions. Overall purchases of red and processed meat (35%) and dairy products (19%) were responsible for the greatest proportion of emissions. The age group of the primary household shopper as well as household size were predictors of per capita dietary emissions — households with primary shoppers > 65 years had, on average, 33% (95% CI: 20% to 49%) higher per capita dietary emissions, compared to households with primary shoppers 34 years; and every additional household member was associated with, on average, 11% (95% CI: 9% to 13%) lower per capita dietary emissions. We have shown in this large representative sample of New Zealand households that purchases of just two food groups — red and processed meat, and dairy — were responsible for approximately half of dietary greenhouse gas emissions. Larger households had lower per capita dietary greenhouse gas emissions, and older shoppers had relatively higher greenhouse gas emissions. Whilst similar associations have been reported elsewhere more research is needed to confirm these latter findings. With enhanced understanding of the observed association between age of a household’s primary shopper and per capita dietary emissions, interventions may be devised that encourage shoppers to purchase lower-emitting foods, particularly less meat and dairy.

Rank-order concordance among conflicting emissions estimates for informing flight choice

Porvair makes environmental improvements across its global operations

At present scenario, estimation of Greenhouse Gas (GHG) emission in the ambient air has becomes a major concern. Emission of GHG has the direct linkage with ambient air pollution and also poses global environmental threats and challenges. Though several scientists are working to mitigate the emission of GHGs but till date no mitigation/management plan has been implemented in global scale. The emission of GHGs are in general from multiple sectors like energy, industry, waste management plant, agricultural sector etc. The major GHGs are methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O). In the present study GHG (CH4, CO2 and N2O) fluxes have been reviewed from wastewater treatment plant (WWTP), constructed wetlands (CWs) and irrigated rice fields (IRF) in India and compared with other countries like Australia, Europe and China. The emission of CH4, CO2 and N2O fluxes from WWTP in Australian condition varied in an average from 0 to 111, 0 to 769 and 0 to 3 ton/year respectively whereas in Indian condition CH4 and N2O fluxes varied in an average from 0 to 6, and 0 to 0.01 ton/year. The higher emission of CH4 and N2O in Australia might be due to higher capacity of WWTP and advance biological treatment plant as compared to India. In Indian and China climatic condition the emission of CH4, CO2 and N2O fluxes from IRF varied from 107 × 104 to 110 × 104, 2116 × 104 to 6096 × 104 and 4 × 104 to 5 × 104, 644 × 104 to 1202 × 104, 205 × 104 to 1208 × 104 and 29 × 104 to 41 × 104 ton/year respectively. The higher fluxes of GHG w.r.t CH4 and N2O might be due to continuous flooding in China, application of nitrogen fertilizers in large scale in the rice field, and likely to be due to overburden pressure for production of rice as compared to India. CWs are the well-known natural CH4 producer in the atmosphere. The emission of CH4 from CWs in India and Europe varied from 46 to 1103 and negative to 38,000 mg/m2/day respectively. CH4 emission depends on tropical coastal wetland condition and type of surface flow in the wetland. India is fewer producers to GHGs as compared to other countries. Appropriate management plan will further reduce the emission of GHGs as well as ambient air pollution.

Understanding spatial and temporal variations of greenhouse gas (GHG) emissions at local level is important for both companies in the agri-food sector working to improve sustainability in their supply chains and local governments following a low-carbon development pathway. For this reason, it is necessary to count with methodologies that do not only estimate GHG emissions, but provide analytics about their location and temporal variations. Factors such as spatial distribution of farms, variations on the requirement of inputs depending on the age of the farms, as well as transportation distances for the main and complementary products, should be assessed at farm level. To accomplish this, spatial and temporal analytics can be incorporated into life cycle assessment (LCA) by joining it with geographic information systems (GIS). This paper explores how spatial statistics tools can be applied to identify spatial and temporal trends in GHG emission results obtained from an LCA conducted on cocoa farming in the region of San Martin in Peru. Results indicate that it is possible to identify temporal and spatial trends of statistically significant clusters of farms with high GHG emissions (hot spot analysis).