Fluid-phase-equilibrium prediction of fluorocompound-containing binary systems with the predictive E-PPR78 model

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

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

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Estimating the viscosity of pure refrigerants and their mixtures by free-volume theory

The decrease in the level of greenhouse gas (GHG) emissions from industry and agriculture is one of the biggest challenges that European Union (EU) countries have to face. Their economic development should occur under the conditions of limiting the pressure on the environment. The agricultural and industrial sectors play a key role in ensuring food security, technological progress, job security, social well-being, economic competitiveness, and sustainable development. The main purpose of this article was to identify and compare the level, trends, and variability in greenhouse gas emissions from industry and agriculture in EU countries in 2010–2019, to create classes of countries with similar gas emissions, and to analyze the average values of their economic conditions. The original contribution to the article was to investigate whether there is a relationship between the level of greenhouse gas emissions and the economic development of countries and other economic indicators characterizing the sectors of industry and agriculture. Empirical data were obtained from the Eurostat and Ilostat databases. Basic descriptive statistics, classification methods, multiple regression, and correlation methods were used in the study. The industrial and agricultural sectors in EU countries emit similar amounts of greenhouse gases into the environment. In the years 2010–2019, the percentage share of emissions from these sectors in total gas emissions was growing dynamically, but no evidence was found indicating that those countries that emitted the most greenhouse gases significantly reduced their emissions in the decade under review. Moreover, EU countries are still significantly and invariably differentiated in this respect. Greenhouse gas emissions from industry and agriculture are influenced by the economic characteristics of these sectors, such as the level of GDP per capita, the scale of investment by enterprises, the expenditure on research and development, as well as employment in these sectors. The findings of this study show that total greenhouse gas emissions from all sources increase with countries’ economic growth, while a higher level of support of EU countries for research and development, and a greater share of employment in both industry and agriculture, translate into higher greenhouse gas emissions from these sectors. These conclusions may be useful for decision makers in developed and developing countries, as well as those in the industrial and agricultural sectors, in controlling and verifying the possible causes of greenhouse gas emissions in terms of the need to reduce their negative role on the environment and human health.

Over the last decades, all countries have pursued an ambitious climate policy, thus showing a growing concern about climate change, global warming, greenhouse gas (GHG) emissions, or environmental taxes. Water, air, and soil pollution caused by gas emissions directly affect human health, but also the economies of states. As people’s ability to adapt to novel changes becomes increasingly difficult, globally, they are constantly trying to reduce their greenhouse gas emissions in a variety of ways. Environmental taxes, in general, and energy taxes, in particular, are considered effective tools, being recommended by specialists, among other instruments used in environmental policy. The aim of this research is to assess, empirically, the influence of environmental taxes levels on greenhouse gas emissions in 28 European countries, with a time span between 1995 and 2019. Regarding the empirical research, the proposed methods are related to Autoregressive Distributed Lag (ARDL) models in panel data and also at country level. At panel level, we used the estimation of non-stationary heterogeneous panels and also the dynamic common-correlated effects model with heterogeneous coefficients over cross-sectional units and time periods. The results obtained show that the increase in environmental taxes leads, in most countries, to a decrease in greenhouse gas emissions. To test the robustness of our results, we have included supplementary economic and social control variables in the model, such as gross domestic product (GDP), population density, exports, or imports. Overall, our paper focuses on the role of environmental policy decisions on greenhouse gas emissions, the results of the study showing, in most cases, an inverse impact of the taxation level on the reduction of gas emissions.

Embodied GHG emissions of buildings – The hidden challenge for effective climate change mitigation

Two equations of state and four mixing rules are applied to the calculation of the bubble point pressure of several refrigerant mixtures. An equation of state proposed by one of the authors, known as the PTV equation, and a modified Soave-Redlich-Kwong equation of state, known as Predictive Soave-Redlich-Kwong (PSRK), have been used. The mixing rules considered in the study include the classic van der Waals mixing rule with one and with two parameters for the PTV equation, and a model that includes the excess Gibbs free energy for the PSRK equation. Eighteen data sets from the literature for five binary refrigerant mixtures containing R134A (CH2FCF3) were considered for analysis. A special program was implemented for these calculations in which the fundamental equation for phase equilibria, the equality of fugacity of each component in all phases, was applied. Correlations for the interaction parameters as functions of the acentric factor are proposed. We present conclusions about usefulness of the different models and a recommendation for the best equation of state + mixing rule combination for correlating vapor-liquid equilibrium in the refrigerant mixtures studied.

Executive Summary: The California Climate Action Registry, which was initially established in 2000 and began operation in Fall 2002, is a voluntary registry for recording annual greenhouse gas (GHG) emissions. The purpose of the Registry is to assist California businesses and organizations in their efforts to inventory and document emissions in order to establish a baseline and to document early actions to increase energy efficiency and decrease GHG emissions. The State of California has committed to use its ''best efforts'' to ensure that entities that establish GHG emissions baselines and register their emissions will receive ''appropriate consideration under any future international, federal, or state regulatory scheme relating to greenhouse gas emissions.'' Reporting of GHG emissions involves documentation of both ''direct'' emissions from sources that are under the entity's control and indirect emissions controlled by others. Electricity generated by an off-site power source is consider ed to be an indirect GHG emission and is required to be included in the entity's report. Registry participants include businesses, non-profit organizations, municipalities, state agencies, and other entities. Participants are required to register the GHG emissions of all operations in California, and are encouraged to report nationwide. For the first three years of participation, the Registry only requires the reporting of carbon dioxide (CO2) emissions, although participants are encouraged to report the remaining five Kyoto Protocol GHGs (CH4, N2O, HFCs, PFCs, and SF6). After three years, reporting of all six Kyoto GHG emissions is required. The enabling legislation for the Registry (SB 527) requires total GHG emissions to be registered and requires reporting of ''industry-specific metrics'' once such metrics have been adopted by the Registry. The Ernest Orlando Lawrence Berkeley National Laboratory (Berkeley Lab) was asked to provide technical assistance to the California Energy Commission (Energy Commission) related to the Registry in three areas: (1) assessing the availability and usefulness of industry-specific metrics, (2) evaluating various methods for establishing baselines for calculating GHG emissions reductions related to specific actions taken by Registry participants, and (3) establishing methods for calculating electricity CO2 emission factors. The third area of research was completed in 2002 and is documented in Estimating Carbon Dioxide Emissions Factors for the California Electric Power Sector (Marnay et al., 2002). This report documents our findings related to the first areas of research. For the first area of research, the overall objective was to evaluate the metrics, such as emissions per economic unit or emissions per unit of production that can be used to report GHG emissions trends for potential Registry participants. This research began with an effort to identify methodologies, benchmarking programs, inventories, protocols, and registries that u se industry-specific metrics to track trends in energy use or GHG emissions in order to determine what types of metrics have already been developed. The next step in developing industry-specific metrics was to assess the availability of data needed to determine metric development priorities. Berkeley Lab also determined the relative importance of different potential Registry participant categories in order to asses s the availability of sectoral or industry-specific metrics and then identified industry-specific metrics in use around the world. While a plethora of metrics was identified, no one metric that adequately tracks trends in GHG emissions while maintaining confidentiality of data was identified. As a result of this review, Berkeley Lab recommends the development of a GHG intensity index as a new metric for reporting and tracking GHG emissions trends.Such an index could provide an industry-specific metric for reporting and tracking GHG emissions trends to accurately reflect year to year changes while protecting proprietary data. This GHG intensity index changes while protecting proprietary data. This GHG intensity index would provide Registry participants with a means for demonstrating improvements in their energy and GHG emissions per unit of production without divulging specific values. For the second research area, Berkeley Lab evaluated various methods used to calculate baselines for documentation of energy consumption or GHG emissions reductions, noting those that use industry-specific metrics. Accounting for actions to reduce GHGs can be done on a project-by-project basis or on an entity basis. Establishing project-related baselines for mitigation efforts has been widely discussed in the context of two of the so-called ''flexible mechanisms'' of the Kyoto Protocol to the United Nations Framework Convention on Climate Change (Kyoto Protocol) Joint Implementation (JI) and the Clean Development Mechanism (CDM).

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.

As a means to help systematically lower anthropogenic Greenhouse gas (GHG) emissions, accurate and precise GHG emission prediction models have became a key focus of many researchers. The appeal is that the predictive models will inform policymakers, and hopefully, in turn, they will bring about systematic changes. Since the transportation sector is constantly among the top GHG emission contributors, substantial effort in the field has been going into building more accurate and informative GHG prediction models. In this work, we seek to establish a predictive framework of GHG emissions at the road segment or link level of road networks. The key theme of the framework centers around model interpretability and actionability for high-level decision-makers. The main model adopted in this framework is a Discrete Choice Model (DCM). We show that, for the first time, DCM is capable of predicting link-level GHG emission levels on road networks in a parsimonious and effective manner. We also argue that since the goal of most GHG emission prediction models focuses on involving high-level decision-makers to make changes and curb emissions, the DCM-based GHG emission prediction framework is the most suitable framework to high-level decision-makers. The nature of the model framework can provide the decision-makers with ease and clarity to address the high GHG emission level with immediate and impactful strategies.

As a means to help systematically lower anthropogenic Greenhouse gas (GHG) emissions, accurate and precise GHG emission prediction models have became a key focus of many researchers. The appeal is that the predictive models will inform policymakers, and hopefully, in turn, they will bring about systematic changes. Since the transportation sector is constantly among the top GHG emission contributors, substantial effort in the field has been going into building more accurate and informative GHG prediction models. In this work, we seek to establish a predictive framework of GHG emissions at the road segment or link level of road networks. The key theme of the framework centers around model interpretability and actionability for high-level decision-makers. The main model adopted in this framework is a Discrete Choice Model (DCM). We show that, for the first time, DCM is capable of predicting link-level GHG emission levels on road networks in a parsimonious and effective manner. We also argue that since the goal of most GHG emission prediction models focuses on involving high-level decision-makers to make changes and curb emissions, the DCM-based GHG emission prediction framework is the most suitable framework to high-level decision-makers. The nature of the model framework can provide the decision-makers with ease and clarity to address the high GHG emission level with immediate and impactful strategies.

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 ...

Trajectory, driving forces, and mitigation potential of energy-related greenhouse gas (GHG) emissions in China's primary aluminum industry