Introducing demand to supply ratio as a new metric for understanding life cycle greenhouse gas (GHG) emissions from rainwater harvesting systems

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

We suggest a 2D-plot representation combined with life cycle greenhouse gas (GHG) emissions and life cycle cost for various energy conversion technologies. In general, life cycle assessment (LCA) not only analyzes at the use phase of a specific technology, but also covers widely related processes of before and after its use. We use life cycle GHG emissions and life cycle cost (LCC) to compare the energy conversion process for eight resources such as coal, natural gas, nuclear power, hydro power, geothermal power, wind power, solar thermal power, and solar photovoltaic (PV) power based on the reported LCA and LCC data. Among the eight sources, solar PV and nuclear power exhibit the highest and the lowest LCCs, respectively. On the other hand, coal and wind power locate the highest and the lowest life cycle GHG emissions. In addition, we used the 2D plot to show the life cycle performance of GHG emissions and LCCs simultaneously and realized a correlation that life cycle GHG emission is largely inversely proportional to the corresponding LCCs. It means that an expensive energy source with high LCC tends to have low life cycle GHG emissions, or is environmental friendly. For future study, we will measure the technological maturity of the energy sources to determine the direction of the specific technology development based on the 2D plot of LCCs versus life cycle GHG emissions.

Plug-in hybrid electric vehicle (PHEV) technology has the potential to reduce operating cost, greenhouse gas (GHG) emissions, and petroleum consumption in the transportation sector. However, the net effects of PHEVs depend critically on vehicle design, battery technology, and charging frequency. To examine these implications, we develop an optimization model integrating vehicle physics simulation, battery degradation data, and U.S. driving data. The model identifies optimal vehicle designs and allocation of vehicles to drivers for minimum net life cycle cost, GHG emissions, and petroleum consumption under a range of scenarios. We compare conventional and hybrid electric vehicles (HEVs) to PHEVs with equivalent size and performance (similar to a Toyota Prius) under urban driving conditions. We find that while PHEVs with large battery packs minimize petroleum consumption, a mix of PHEVs with packs sized for ∼25–50 miles of electric travel under the average U.S. grid mix (or ∼35–60 miles under decarbonized grid scenarios) produces the greatest reduction in life cycle GHG emissions. Life cycle cost and GHG emissions are minimized using high battery swing and replacing batteries as needed, rather than designing underutilized capacity into the vehicle with corresponding production, weight, and cost implications. At 2008 average U.S. energy prices, Li-ion battery pack costs must fall below $590/kW h at a 5% discount rate or below $410/kW h at a 10% rate for PHEVs to be cost competitive with HEVs. Carbon allowance prices offer little leverage for improving cost competitiveness of PHEVs. PHEV life cycle costs must fall to within a few percent of HEVs in order to offer a cost-effective approach to GHG reduction.

Impacts of alternative fuel combustion in cement manufacturing: Life cycle greenhouse gas, biogenic carbon, and criteria air contaminant emissions

A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies

The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6%–2.0% reduction in annual life cycle GHG emissions at a cost penalty of 5.1%–6.9% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of decarbonization apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6-2.0% reduction in annual life cycle GHG emissions at a cost penalty of 3.2–9.6% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

Life cycle assessment of primary energy demand and greenhouse gas (GHG) emissions of four propylene production pathways in China

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear power but lead to considerably higher costs compared to the cost-optimal solution. Power systems that mitigate life cycle GHG emissions also perform better for most impact categories but have higher ionizing radiation, water use and increased fossil fuel demand driven by nuclear power. This study shows that it is crucial to consider upstream GHG emissions in future assessments, as they represent an inheritable part of total emissions in ambitious energy scenarios that, so far, mainly aim to reduce direct CO2 emissions.

Life cycle greenhouse gas emissions and freshwater consumption of liquefied Marcellus shale gas used for international power generation

This study assesses and compares lifecycle (LC) greenhouse gas (GHG) emissions from the two main railway track construction types: ballasted track and slab track. In this study, preexisting soil conditions are considered, as they significantly influence necessary measures during the construction phase for each type. This study is executed for Austrian boundary conditions with speeds up to 250 km/h. The results show that ballasted track is associated with 11–20% lower LC GHG emissions, whereby the variation in relative emission reduction is associated with additional soil reinforcement treatments due to varying preexisting soil conditions. Poor preexisting soil conditions increase LC GHG emissions by 26%, underlying the necessity to integrate this parameter into the lifecycle assessment of railway track. In contrast to the higher service life of slab track construction, this type amounts to higher masses of concrete and demands more extensive measures for soil enhancement due to the higher stiffness of the track panel. Only in tunnel areas does slab track cause lower GHG emissions since soil reinforcements are not necessary due to an existing concrete base layer after tunnel construction. For both construction types, over 80% of the GHG emissions stem from material production. Hence, circular economy as well as innovations within steel and concrete production processes hold significant potential for reducing GHG emissions.

Impacts of pre-treatment technologies and co-products on greenhouse gas emissions and energy use of lignocellulosic ethanol production

This study estimates the life cycle greenhouse gas (GHG) emissions from the production ofMarcellus shale natural gas and compares its emissions with national average US naturalgas emissions produced in the year 2008, prior to any significant Marcellus shaledevelopment. We estimate that the development and completion of a typical Marcellusshale well results in roughly 5500 t of carbon dioxide equivalent emissions or about 1.8 g CO2e/MJ of gas produced, assuming conservative estimates of the production lifetime of a typical well.This represents an 11% increase in GHG emissions relative to average domestic gas (excludingcombustion) and a 3% increase relative to the life cycle emissions when combustion is included.The life cycle GHG emissions of Marcellus shale natural gas are estimated to be 63–75 g CO2e/MJ of gas produced withan average of 68 g CO2e/MJ of gas produced. Marcellus shale natural gas GHG emissions are comparable tothose of imported liquefied natural gas. Natural gas from the Marcellus shale hasgenerally lower life cycle GHG emissions than coal for production of electricity inthe absence of any effective carbon capture and storage processes, by 20–50%depending upon plant efficiencies and natural gas emissions variability. There issignificant uncertainty in our Marcellus shale GHG emission estimates due to eventualproduction volumes and variability in flaring, construction and transportation.

Biomaterials and raw earth have demonstrated a promising potential for improving various thermal properties of plastering mortars used in buildings. The objective of this research was the evaluation of the thermal-energy performances and life cycle greenhouse gas (GHG) emissions of different mixtures of engineered, bio-based earth mortars composed of bamboo particles, earth, and different cementitious materials. Four mixtures were assessed: mortars without bamboo particles (matrix), and mortars containing 3%, 6%, or 9% of bamboo particles by volume. The bulk density and thermal conductivity values obtained for the matrix and mortars with the highest percentage of bamboo particles (9%) were 1704.13 and 1471.80 kg/m3, and 0.62 and 0.43 W/M·K, respectively. Based on experimental results, thermal-energy simulations were carried out using a social housing project as a case study. The simulations evaluated different climate conditions and applied life cycle GHG emissions assessment methodology. Compared with typical cement and lime plastering mortars, the proposed bio-based earth mortars presented a superior thermal-energy performance and lower GHG emissions, particularly the 9% bamboo particles mixture. GHG emissions reached a maximum decrease of 28%. The main scientific contribution of this research is the presentation of an engineered, bio-based earth mortar that can be manufactured using local raw materials available in most developing countries with significant housing demands. The method used, based on experimental research, thermal-energy analysis, and life cycle GHG emissions, may be used for evaluating other innovative materials. It was verified that even with thin plastering in buildings, it is possible to achieve energy efficiency gains and to reduce GHG emissions.

Increased E-commerce and demand for contactless delivery during the COVID-19 pandemic have fueled interest in robotic package delivery. We evaluate life cycle greenhouse gas (GHG) emissions for automated suburban ground delivery systems consisting of a vehicle (last-mile) and a robot (final-50-feet). Small and large cargo vans (125 and 350 cubic feet; V125 and V350) with an internal combustion engine (ICEV) and battery electric (BEV) powertrains were assessed for three delivery scenarios: (i) conventional, human-driven vehicle with human delivery; (ii) partially automated, human-driven vehicle with robot delivery; and (iii) fully automated, connected automated vehicle (CAV) with robot delivery. The robot's contribution to life cycle GHG emissions is small (2-6%). Compared to the conventional scenario, full automation results in similar GHG emissions for the V350-ICEV but 10% higher for the V125-BEV. Conventional delivery with a V125-BEV provides the lowest GHG emissions, 167 g CO2e/package, while partially automated delivery with a V350-ICEV generates the most at 486 g CO2e/package. Fuel economy and delivery density are key parameters, and electrification of the vehicle and carbon intensity of the electricity have a large impact. CAV power requirements and efficiency benefits largely offset each other, and automation has a moderate impact on life cycle GHG emissions.