Estimating Greenhouse Gases from Roadway Transportation—Methodology Overview

Blue revolution for food security under carbon neutrality: A case from the water-saving and drought-resistance rice

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

Porvair makes environmental improvements across its global operations

The traditional upscaling approach to greenhouse gas (GHG) emission estimates of inland waters is imprecise, but more precise methods based on environmental drivers are a longstanding challenge. Mexico lacks GHG emission estimates for its inland waters, and only sparse but scientifically validated information is available. This study provides the first GHG emission estimates from Mexican inland waters using 4275 GHG flux measurements from 26 distinctive waterbodies and one local and another global surface area dataset (INEGI and HydroLAKES). GHG emission factors were calculated and subsequently upscaled to estimate total national GHG emissions from the inland waters and compare to other emission measures based on mean global emission factors or size-productivity weighted (SPW) models. Mean (standard error) annual fluxes from all inland waters were 2.2 (5.3) kg CO2 m−2 yr−1, 0.6 (1.14) kg CH4 m−2 yr−1, and 1.0 × 10−3 (6.0 × 10−4) kg N2O m−2 yr−1. Estimates for natural waterbodies are annual average release rates between 74 (87) and 139 (163.23) Tg CO2eq while artificial waterbodies reach between 32 (2) and 21 (21) Tg CO2eq according to INEGI and HydroLAKES datasets, respectively. Considerable uncertainty was determined in the calculated mean emission factor, mostly for anthropogenic emissions. Waterbody area and chlorophyll a concentration were used as proxies to model CO2 and CH4 fluxes through regression analysis. According to SPW and IPCC models, computed mean annual CH4 emission factors were close to our estimates and exhibited a strong influence from eutrophication. In a likely scenario of increased eutrophication in Mexico, an increase in total net emissions from inland waters could be expected.

ABSTRACTSouth Korea has the tenth highest greenhouse gas (GHG) emissions worldwide, of which 16% originates from the road sector. Existing estimation methods of road GHG emissions have various limitations, such as low accuracy or the ability to only estimate GHG emissions within a limited area. Therefore, this study aimed to develop a methodology to estimate GHG emissions while considering various geometric designs of roads, including both vertical and horizontal alignment. The developed method is more objective and reliable than existing methodologies that consider only vertical alignment. First, Lamm's theory on travel speed profiles was applied to predict GHG emissions. Then, this study attempted to overcome the limited spatial estimation capacity of existing methods by considering upstream and downstream geometric design parameters simultaneously. Second, this study used the GHG operation mode extracted from the MOtor Vehicle Emission Simulator (MOVES), a modeling system that estimates emissions for mobile sources at the national, county, and project levels for criteria air pollutants, GHGs, and air toxicity. The operation mode includes vehicle type, fuel, and other factors, and is designed to estimate GHG emissions at 1-s intervals. Based on the results of the analysis, the effectiveness of the new method was compared to existing methods using an economic analysis (e.g., cost–benefits from the reduced emissions). This study presents a method for performing sensitive estimations of GHG emissions according to the geometric design of roads, which can be used to collect more accurate data on GHG emissions.

Diversity in reservoir surface morphology and climate limits ability to compare and upscale estimates of greenhouse gas emissions

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 %).

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

The estimation and control of vehicle emissions play an important role in the sustainable development of an urban area. Many studies have shown that without a balance between vehicle usage and vehicle emissions, urban areas will never be able to reach a sustainable development. However, for planning purposes professionals have struggled with the proper modeling and estimation of vehicle emissions in an urban area. The focus of this paper is to present a new modeling procedure for estimating vehicle emissions based on individual vehicle interactions in a traffic stream. The model microsimulates these interactions and then translates them into consequent energy consumption and pollutant emissions. The main feature of this model is that it calculates the effects of transient changes in power on vehicle emissions. It divides power into 34 bins and speed into 20 bins covering the three vehicular events of acceleration, deceleration, and cruise. It does the emission calculation at every second and in 7.5 meters cells and accumulates the results into 30-meter segments and 15 minutes interval. The model takes into consideration grades, malfunctioning vehicles, coldlwarm starts, enrichment cycles, and types of vehicles. It has a running evaporative emissions module and a resting, hot soak, and diurnal evaporative emissions by location. Among its inputs are the EPA's three-cities distribution of speeds and accelerations, The CARB stratified arterial and freeway trajectories, the CMEM model used to construct emission arrays by vehicle type, speed , grade and power bin, West Virginia University truck power distributions and West Virginia University truck and bus emissions. The output shows the emissions in terms of HC, CO, and NOx for each road segment of a link for each time interval.

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

Intended nationally determined contributions (INDCs) are a new strategy for mitigating climate change. Many international organizations and scholars have assessed the possibility of holding the increase in global average temperature to well below 2°C based on INDCs. Although the conclusions of these assessments are consistent, there are still large differences among the assessment results. For example, the global greenhouse gas emissions in 2030 estimated by INDCs are between 47.1–66.5 GtCO2 eq, and the temperature increase at the end of the 21st century estimated by INDCs is between 2.4–4.0°C; the inconsistency represented by these ranges is not conducive to an accurate assessment of the contributions of the current INDCs to global warming mitigation or to the further development of emissions reduction programs. By summarizing the existing studies, we found that the main reasons for the differences in estimates of global greenhouse gas emissions in 2030 made using INDCs are as follows: (1) The studies interpreted INDCs differently, which is attributable to three reasons: The studies (a) made different assumptions for the unquantifiable INDCs; (b) ignored or used different methods to estimate the emissions not covered by INDCs; and (c) used different amounts of INDCs because the studies were performed at different times. (2) The studies used different databases that include different greenhouse gases, accounting methods and data sources to estimate historical greenhouse gas emissions. (3) The studies used different methods for estimating greenhouse gas emissions and removals related to land use, land-use change and forestry (LULUCF). (4) The studies used different values of the global warming potential. Additionally, the main reasons for the differences in the predictions of the temperature increase at the end of the 21st century based on INDCs are as follows: (1) Differences in the estimations of greenhouse gas emissions in 2030 based on INDCs and (2) different methods of extrapolating global greenhouse gas emissions to 2100. There are three main extrapolation methods: one is to maintain the net present value of the carbon price in 2030 and then extrapolate the greenhouse gas emissions to 2100; another is to maintain the decarbonization rate of a certain period of history and then extrapolate the greenhouse gas emissions to 2100; the third is to match the emissions reduction scenario with the current INDC emissions reduction scenario from the IPCC AR5 scenario database and then use the matching emissions reduction scenario as the current INDC emissions reduction scenario. The use of different methods of extrapolating carbon emissions is one of the main reasons for the differences in the prediction results. (3) Differences in the methods for predicting the effects of greenhouse gas emissions on temperature. Statistical methods and simulation methods are the two main prediction methods; they use different calculation methods, which led to the difference in the prediction results. Therefore, the following points are worth noting: (1) Most importantly, to the extent possible, countries should submit absolute emissions reduction targets as much as possible; nonquantifiable INDCs without detailed methods descriptions and data introductions should not be submitted; (2) authorities should recommend certain data sets that are the most suitable for INDC accounting; (3) a global warming potential should be designated to avoid differences in greenhouse gas estimates due to the use of different criteria; and (4) to the extent possible, future research should adopt simulation methods for predicting the impact of global greenhouse gas emissions on temperature.

A numerical model was developed to comprehensively predict greenhouse gas (GHG) emissions from water resource recovery facilities. An existing activated sludge model was extended to include a nitrifier-denitrification process and carbon dioxide (CO₂) as a state variable. The bioreactor model was coupled to a process-based digester model and an empirical model of indirect CO₂emissions. Direct emissions were approximately 90% of total GHG emissions for a plantwide simulation using the Modified Ludzack-Ettinger process. Biogenic CO₂, nitrous oxide (N₂O), and methane (CH₄) represented 10, 43, and 34% of total emissions. Simulating a dissolved oxygen controlled closed-loop system reduced both sensitivity and uncertainty of GHG emissions. Nitrous oxide emissions were much more sensitive under different design and operating conditions compared to CH₄and CO₂, indicating a significant mitigation potential. An uncertainty analysis found that the uncertainty in GHGs emissions estimates could be significant. Nitrous oxide emissions dominated in both magnitude and uncertainty.

The increasing vehicle usage has brought about a sharp increase in greenhouse gas (GHG) emissions of vehicles, which brings severe challenges to the sustainable development of road transportation in Chinese counties. Low-carbon transportation planning is an essential strategy for carbon control from the source of carbon emissions and is crucial to the full transition to a low-carbon future. For transportation planning designers, a quick and accurate estimation of carbon emissions under different transportation planning schemes is a prerequisite to determine the optimal low-carbon transportation development plan. To address this issue, a novel prediction method of hourly GHG emissions over the urban roads network was constructed in this paper. A case study was conducted in Changxing county, and the results indicate the effectiveness of our proposed method. Furthermore, we applied the same approach to 30 other counties in China to analyze the influencing factors of emissions from urban road networks in Chinese counties. The analysis results indicate that the urban road mileage and arterial road ratio are the two most important factors affecting road network GHG emissions in road traffic planning process. Moreover, the method was employed to derive peak hour emission coefficients that can be used to quickly estimate daily or annual GHG emissions. The peak hour emission of CO2, CH4, and N2O accounts for approximately 9–10%, 8.5–10.5%, 5.5–7.5% of daily emissions, respectively. It is expected that the findings from this study would be helpful for establishing effective carbon control strategies in the transportation planning stage to reduce road traffic GHG emissions in counties.

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

Global warming/climate change is the greatest environmental threat of our time. Rapidly developing aquaculture sector is an anthropogenic activity, the contribution of which to global warming is little understood, and estimation of greenhouse gases (GHGs) emission from the aquaculture ponds is a key practice in predicting the impact of aquaculture on global warming. A comprehensive methodology was developed for sampling and simultaneous analysis of GHGs, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from the aquaculture ponds. The GHG fluxes were collected using cylindrical acrylic chamber, air pump, and tedlar bags. A cylindrical acrylic floating chamber was fabricated to collect the GHGs emanating from the surface of aquaculture ponds. The sampling methodology was standardized and in-house method validation was established by achieving linearity, accuracy, precision, and specificity. GHGs flux was found to be stable at 10±2°C of storage for 3days. The developed methodology was used to quantify GHGs in the Pacific white shrimp Penaeus vannamei and black tiger shrimp Penaeus monodon culture ponds for a period of 4months. The rate of emission of carbon dioxide was found to be much greater when compared to other two GHGs. Average GHGs emission in gha-1day-1 during the culture was comparatively high in P.vannamei culture ponds.