A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns.

A synthetic population is a simplified microscopic representation of an actual population. Statistically representative at the population level, it provides valuable inputs to simulation models (especially agent-based models) in research areas such as transportation, land use, economics, and epidemiology. This article describes the datasets from the Synthetic Sweden Mobility (SySMo) model using the state-of-art methodology, including machine learning (ML), iterative proportional fitting (IPF), and probabilistic sampling. The model provides a synthetic replica of over 10 million Swedish individuals (i.e., agents), their household characteristics, and activity-travel plans. This paper briefly explains the methodology for the three datasets: Person, Households, and Activity-travel patterns. Each agent contains socio-demographic attributes, such as age, gender, civil status, residential zone, personal income, car ownership, employment, etc. Each agent also has a household and corresponding attributes such as household size, number of children ≤ 6 years old, etc. These characteristics are the basis for the agents' daily activity-travel schedule, including type of activity, start-end time, duration, sequence, the location of each activity, and the travel mode between activities.

If Electric Cars Are Good for Reducing Emissions, They Could Be Even Better with Electric Roads.

This research investigates carbon footprint impacts for full fleet electrification of Swedish passenger car travel in combination with different charging conditions, including electric road system (ERS) that enables dynamic on-road charging. The research applies a prospective life cycle analysis framework for estimating carbon footprints of vehicles, fuels, and infrastructure. The framework includes vehicle stock turnover modeling of fleet electrification and modeling of optimal battery capacity for different charging conditions based on Swedish real-world driving patterns. All new car sales are assumed to be electric after 2030 following phase-out policies for gasoline and diesel cars. Implementing ERS on selected high-traffic roads could yield significant avoided emissions in battery manufacturing compared to the additional emissions in ERS construction. ERS combined with stationary charging could enable additional reductions in the cumulative carbon footprint of about 12-24 million tons of CO2 over 30 years (2030-2060) compared to an electrified fleet only relying on stationary charging. The range depends on uncertainty in emission abatement in global manufacturing, where the lower is based on Paris Agreement compliance and the higher on current climate policies. A large share of the reduction could be achieved even if only a small share of the cars adopts the optimized battery capacities.

Disparities in travel times between car and transit: Spatiotemporal patterns in cities.

Cities worldwide are pursuing policies to reduce car use and prioritise public transit (PT) as a means to tackle congestion, air pollution, and greenhouse gas emissions. The increase of PT ridership is constrained by many aspects; among them, travel time and the built environment are considered the most critical factors in the choice of travel mode. We propose a data fusion framework including real-time traffic data, transit data, and travel demand estimated using Twitter data to compare the travel time by car and PT in four cities (São Paulo, Brazil; Stockholm, Sweden; Sydney, Australia; and Amsterdam, the Netherlands) at high spatial and temporal resolutions. We use real-world data to make realistic estimates of travel time by car and by PT and compare their performance by time of day and by travel distance across cities. Our results suggest that using PT takes on average 1.4-2.6 times longer than driving a car. The share of area where travel time favours PT over car use is very small: 0.62% (0.65%), 0.44% (0.48%), 1.10% (1.22%) and 1.16% (1.19%) for the daily average (and during peak hours) for São Paulo, Sydney, Stockholm, and Amsterdam, respectively. The travel time disparity, as quantified by the travel time ratio [Formula: see text] (PT travel time divided by the car travel time), varies widely during an average weekday, by location and time of day. A systematic comparison between these two modes shows that the average travel time disparity is surprisingly similar across cities: [Formula: see text] for travel distances less than 3 km, then increases rapidly but quickly stabilises at around 2. This study contributes to providing a more realistic performance evaluation that helps future studies further explore what city characteristics as well as urban and transport policies make public transport more attractive, and to create a more sustainable future for cities.

Water impacts of U.S. biofuels: Insights from an assessment combining economic and biophysical models.

Biofuels policies induce land use changes (LUC), including cropland expansion and crop switching, and this in turn alters water and soil management practices. Policies differ in the extent and type of land use changes they induce and therefore in their impact on water resources. We quantify and compare the spatially varying water impacts of biofuel crops stemming from LUC induced by two different biofuels policies by coupling a biophysical model with an economic model to simulate the economically viable mix of crops, land uses, and crop management choices under alternative policy scenarios. We assess the outputs of an economic model with a high-resolution crop-water model for major agricultural crops and potential cellulosic feedstocks in the US to analyze the impacts of three alternative policy scenarios on water balances: a counterfactual 'no-biofuels policy' (BAU) scenario, a volumetric mandate (Mandate) scenario, and a clean fuel-intensity standard (CFS) scenario incentivizing fuels based on their carbon intensities. While both biofuel policies incentivize more biofuels than in the counterfactual, they differ in the mix of corn ethanol and advanced biofuels from miscanthus and switchgrass (more corn ethanol in Mandate and more cellulosic biofuels in CFS). The two policies differ in their impact on irrigated acreage, irrigation demand, groundwater use and runoff. Net irrigation requirements increase 0.7% in Mandate and decrease 3.8% in CFS, but in both scenarios increases are concentrated in regions of Kansas and Nebraska that rely upon the Ogallala aquifer for irrigation water. Our study illustrates the importance of accounting for the overall LUC and shifts in agricultural production and management practices in response to policies when assessing the water impacts of biofuels.

Recent Trends in Water Use and Production for California Oil Production.

Recent droughts and concerns about water use for petroleum extraction renew the need to inventory water use for oil production. We quantified water volumes used and produced by conventional oil production and hydraulic fracturing (HF) in California. Despite a 25% decrease in conventional oil production from 1999 to 2012, total water use increased by 30% though much of that increase was derived from reuse of produced water. Produced water volumes increased by 50%, with increasing amounts disposed in unlined evaporation ponds or released to surface water. Overall freshwater use (constituting 1.2% of the state's nonagricultural water consumption) increased by 46% during this period due to increased freshwater-intensive tertiary oil production. HF has been practiced in California for more than 30 years, accounting for 1% of total oil production in 2012 from mostly directional and vertical wells. Water use intensity for HF wells in California averaged at 3.5 vol water/vol oil production in 2012 and 2.4 vol/vol in 2013, higher than the range from literature estimates and net water use intensity of conventional production (1.2 vol/vol in 2012). Increasing water use and disposal for oil production have important implications for water management and have potentially adverse health, environmental, and ecological impacts.

Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for U.S. Petroleum Fuels.

Greenhouse gas (GHG) regulations affecting U.S. transportation fuels require holistic examination of the life-cycle emissions of U.S. petroleum feedstocks. With an expanded system boundary that included land disturbance-induced GHG emissions, we estimated well-to-wheels (WTW) GHG emissions of U.S. production of gasoline and diesel sourced from Canadian oil sands. Our analysis was based on detailed characterization of the energy intensities of 27 oil sands projects, representing industrial practices and technological advances since 2008. Four major oil sands production pathways were examined, including bitumen and synthetic crude oil (SCO) from both surface mining and in situ projects. Pathway-average GHG emissions from oil sands extraction, separation, and upgrading ranged from ∼6.1 to ∼27.3 g CO2 equivalents per megajoule (in lower heating value, CO2e/MJ). This range can be compared to ∼4.4 g CO2e/MJ for U.S. conventional crude oil recovery. Depending on the extraction technology and product type output of oil sands projects, the WTW GHG emissions for gasoline and diesel produced from bitumen and SCO in U.S. refineries were in the range of 100-115 and 99-117 g CO2e/MJ, respectively, representing, on average, about 18% and 21% higher emissions than those derived from U.S. conventional crudes. WTW GHG emissions of gasoline and diesel derived from diluted bitumen ranged from 97 to 103 and 96 to 104 g CO2e/MJ, respectively, showing the effect of diluent use on fuel emissions.

Long-term shifts in life-cycle energy efficiency and carbon intensity.

The quantity of primary energy needed to support global human activity is in large part determined by how efficiently that energy is converted to a useful form. We estimate the system-level life-cycle energy efficiency (EF) and carbon intensity (CI) across primary resources for 2005-2100. Our results underscore that although technological improvements at each energy conversion process will improve technology efficiency and lead to important reductions in primary energy use, market mediated effects and structural shifts toward less efficient pathways and pathways with multiple stages of conversion will dampen these efficiency gains. System-level life-cycle efficiency may decrease as mitigation efforts intensify, since low-efficiency renewable systems with high output have much lower GHG emissions than some high-efficiency fossil fuel systems. Climate policies accelerate both improvements in EF and the adoption of renewable technologies, resulting in considerably lower primary energy demand and GHG emissions. Life-cycle EF and CI of useful energy provide a useful metric for understanding dynamics of implementing climate policies. The approaches developed here reiterate the necessity of a combination of policies that target efficiency and decarbonized energy technologies. We also examine life-cycle exergy efficiency (ExF) and find that nearly all of the qualitative results hold regardless of whether we use ExF or EF.

Life cycle water consumption and withdrawal requirements of ethanol from corn grain and residues.

We assessed the water requirements of ethanol from corn grain and crop residue. Estimates are explicit in terms of sources-green (GW) and blue (BW) water, consumptive and nonconsumptive requirements across the lifecycle, including evapotranspiration, application and conveyance losses, biorefinery uses, and water use of energy inputs, and displaced requirements or credits due to coproducts. Ethanol consumes 50-146 L/vehicle kilometer traveled (VKT) of BW and 1-60 L/VKT of GW for irrigated corn and 0.6 L/VKT of BW and 70-137 L/VKT of GW for rain-fed corn after coproduct credits. Extending the system boundary to consider application and conveyance losses and the water requirements of embodied energy increases the total BW withdrawal from 23% to 38% and BW + GW consumption from 5% to 16%. We estimate that, in 2009, 15-19% of irrigation water is used to produce the corn required for ethanol in Kansas and Nebraska without coproduct credits and 8-10% after credits. Harvesting and converting the cob to ethanol reduces both the BW and GW intensities by 13%. It is worth noting that the use of GW is not without impacts, and the water quantity and water quality impacts at the local/seasonal scale can be significant for both fossil fuel and biofuel.

Land use greenhouse gas emissions from conventional oil production and oil sands.

Debates surrounding the greenhouse gas (GHG) emissions from land use of biofuels production have created a need to quantify the relative land use GHG intensity of fossil fuels. When contrasting land use GHG intensity of fossil fuel and biofuel production, it is the energy yield that greatly distinguishes the two. Although emissions released from land disturbed by fossil fuels can be comparable or higher than biofuels, the energy yield of oil production is typically 2-3 orders of magnitude higher, (0.33-2.6, 0.61-1.2, and 2.2 5.1 PJ/ha) for conventional oil production, oil sands surface mining, and in situ production, respectively). We found that land use contributes small portions of GHGs to life cycle emissions of California crude and in situ oil sands production ( <0.4% or < 0.4 gCO2e/MJ crude refinery feedstock) and small to modest portions for Alberta conventional oil (0.1-4% or 0.1-3.4 gCO2e/MJ) and surface mining of oil sands (0.9-11% or 0.8-10.2 gCO2e/MJ).Our estimates are based on assumptions aggregated over large spatial and temporal scales and assuming 100% reclamation. Values on finer spatial and temporal scales that are relevant to policy targets need to account for site-specific information, the baseline natural and anthropogenic disturbance.

Assessment of technologies to meet a low carbon fuel standard.

California's low carbon fuel standard (LCFS) was designed to incentivize a diverse array of available strategies for reducing transportation greenhouse gas (GHG) emissions. It provides strong incentives for fuels with lower GHG emissions, while explicitly requiring a 10% reduction in California's transportation fuel GHG intensity by 2020. This paper investigates the potential for cost-effective GHG reductions from electrification and expanded use of biofuels. The analysis indicates that fuel providers could meetthe standard using a portfolio approach that employs both biofuels and electricity, which would reduce the risks and uncertainties associated with the progress of cellulosic and battery technologies, feedstock prices, land availability, and the sustainability of the various compliance approaches. Our analysis is based on the details of California's development of an LCFS; however, this research approach could be generalizable to a national U.S. standard and to similar programs in Europe and Canada.

Optimizing U.S. mitigation strategies for the light-duty transportation sector: what we learn from a bottom-up model.

Few integrated analysis models examine significant U.S. transportation greenhouse gas emission reductions within an integrated energy system. Our analysis, using a bottom-up MARKet ALocation (MARKAL) model, found that stringent system-wide CO2 reduction targets will be required to achieve significant CO2 reductions from the transportation sector. Mitigating transportation emission reductions can result in significant changes in personal vehicle technologies, increases in vehicle fuel efficiency, and decreases in overall transportation fuel use. We analyze policy-oriented mitigation strategies and suggest that mitigation policies should be informed by the transitional nature of technology adoptions and the interactions between the mitigation strategies, and the robustness of mitigation strategies to long-term reduction goals, input assumptions, and policy and social factors. More research is needed to help identify robust policies that will achieve the best outcome in the face of uncertainties.

Technology innovations and experience curves for nitrogen oxides control technologies.

This paper reviews the regulatory history for nitrogen oxides (NOx) pollutant emissions from stationary sources, primarily in coal-fired power plants. Nitrogen dioxide (NO2) is one of the six criteria pollutants regulated by the 1970 Clean Air Act where National Ambient Air Quality Standards were established to protect public health and welfare. We use patent data to show that in the cases of Japan, Germany, and the United States, innovations in NOx control technologies did not occur until stringent government regulations were in place, thus "forcing" innovation. We also demonstrate that reductions in the capital and operation and maintenance (O&M) costs of new generations of high-efficiency NOx control technologies, selective catalytic reduction (SCR), are consistently associated with the increasing adoption of the control technology: the so-called learning-by-doing phenomena. The results show that as cumulative world coal-fired SCR capacity doubles, capital costs decline to approximately 86% and O&M costs to 58% of their original values. The observed changes in SCR technology reflect the impact of technological advance as well as other factors, such as market competition and economies of scale.

Incorporating exposure models in probabilistic assessment of the risks of premature mortality from particulate matter.

This paper examines the link between the ambient level of particulate pollution and subsequent human health effects and various sources of uncertainty when total exposure is taken into consideration. The exposure simulation model statistically simulates daily personal total exposure to ambient PM and nonambient PM generated from indoor sources. It incorporates outdoor-indoor penetration of PM, contributions of PM from indoor sources, and time-activity patterns for target groups of the population. The model is illustrated for Los Angeles County using recent 1997 monitoring data for both PM(10) and PM(2.5). The results indicate that, on average, outdoor-source PM contributes about 20-25% of the total PM exposure to Los Angeles County individuals not exposed to environmental tobacco smoking (ETS), and about 15% for those who are exposed to ETS. The model computes both the fractional contribution of outdoor concentrations to total exposure and the effect of exposure uncertainties on the estimated slope of the (linear) concentration-response curve in time-series studies for PM health effects. The latter considers the effects of measurement and misclassification error on PM epidemiological time-series studies. The paper compares the predictions of a conventional PM epidemiological model, based solely on ambient concentration measurements at a central monitoring station, and an exposure simulation model, which considers the quantitative relationship between central-monitoring PM concentrations and total individual exposures to particulate matter. The results show that the effects of adjusting from outdoor concentrations to personal exposures and correcting dose-response bias are nearly equal, so that roughly the same premature mortalities associated with short-term exposure to both ambient PM(2.5) and PM(10) in Los Angeles County are predicted with both models. The uncertainty in the slope of the concentration-response curve in the time-series studies is the single most important source of uncertainty in both the ambient- and the exposure-health model.