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Policy Analysis

Long-Run Environmental and Economic Impacts of Electrifying Waterborne Shipping in the United States
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Environmental Science & Technology

Cite this: Environ. Sci. Technol. 2020, 54, 16, 9824–9833
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https://doi.org/10.1021/acs.est.0c03298
Published July 21, 2020

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Abstract

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Emissions from ships in and surrounding ports are a major contributor to urban air pollution in coastal and inland riverside cities. Connecting docked ships to onshore grid electricity and using electric tugboats are two approaches to reduce pollution damages. This paper examines the effects of the widespread adoption of electrification in waterborne shipping. Our study is novel in the use of an equilibrium model of the U.S. energy system to capture the effects of increasing electricity generation to electrify waterborne shipping both with and without a carbon pricing policy. We examine three scenarios, Electrifying in ports, Electrifying in Emission Control Areas, and Electrifying all U.S. vessel fuels, as well as an electrification scenario under carbon pricing, allowing electrification of waterborne shipping to contribute to deeper decarbonization. We find that electrification results in slight carbon emission reductions in early projected years and that the reductions increase as the electric grid evolves out to 2050. We also show that an ambitious scenario of electrifying all U.S. vessel fuels results in up to 65% net reduction in air pollution as we approach 2050, even after accounting for the pollution increase from grid generation. Our baseline results indicate that intensive waterborne shipping electrification can provide considerable social benefits that exceed the costs, especially as the electric grid decarbonizes.

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1. Introduction

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The waterborne transportation sector is essential for global trade, but it also strongly contributes to CO2 emissions and local air pollution. (1−3) Vessels can be among the dirtiest emitters, as they often are burning low-grade fossil fuels. (4−6) Thus, people living or working near ports can be adversely impacted by air pollution, facing premature mortality and increased hospital visits for respiratory, heart, and lung diseases. (7,8) In response to these local health concerns, there has been policy action intended to reduce emissions in the areas around ports in the United States, including Emission Control Areas (ECA), the Diesel Emissions Reduction Act (DERA), and Congestion Mitigation and Air Quality Improvement (CMAQ) programs. (9)
There has been considerable policy discussion in recent years about electrifying port activities using onshore grid power. For example, vessels can plug into the onshore electric grid while docked, and electric tugboats can be used for maneuvering into ports and then plugged into the onshore grid. Other activities can be electrified too, such as cargo handling equipment and short-haul vehicles. Waterborne shipping electrification has been discussed as having great potential to shift pollution from ports (both inland and coastal) and waterways in populated areas to lower-polluting power plants in more remote locations. This policy is already being implemented in a limited way in several ports. For example, Long Beach and Los Angeles both have limited electrification programs for ocean-going vessels. (10,11) Whether there is a net reduction in emissions from electrification depends on the emission intensity (both carbon and local air pollutants) of the fuels used in shipping versus the electricity grid. Hence, a cleaner electric grid raises the likelihood of a net reduction.
This paper uses the well-known National Energy Modeling System (hereafter Yale-NEMS) as the primary research tool. Yale-NEMS is the U.S. Energy Information Administration (EIA)’s NEMS model run on a server at Yale with minor changes made for our analysis (e.g., adding electricity consumption by ships from the onshore grid to reflect the current status of waterborne shipping electrification). We address two main questions in our analysis: (1) would electrifying waterborne vessels lead to lower net emissions of CO2 and local air pollutants in realistic scenarios of the future energy system and (2) what are the associated benefits and costs? We examine three waterborne shipping electrification scenarios in the U.S. energy system: (1) electrifying auxiliary power for vessels docked in ports; (2) electrifying auxiliary and primary engine fuels within the extended areas from the ports (e.g., through additional electrified tugboats); (3) electrifying all vessel fuels accrued to the U.S. energy system (e.g., perhaps someday through vessels with electric storage). In this study, we focus on electrifying the vessels themselves, as these are the largest source of emissions from ports, (9) but we note that deeper decarbonization could require the electrification of all port activities.
Our work is novel in several ways. It is the first study that explicitly models the effects of waterborne shipping electrification into the future using realistic projections of how the future electricity system in different regions of the United States would evolve out to 2050. Importantly, we examine scenarios with and without carbon pricing, allowing us to make full use of the capabilities of Yale-NEMS. This paper is also the first study to explore more intensive electrification of waterborne shipping. As policymakers consider deeper decarbonization across nearly all sectors of the economy, it is important to understand the effects of such intensive electrification scenarios with carbon pricing. (12)
Yale-NEMS is a general equilibrium model of the U.S. energy markets (interacting with international energy markets), subject to a set of current policies, resource constraints, and technological advancement. Continually developed by the U.S. EIA, the model has a broad geographic scope, detailed modeling of the energy markets, and comprehensive inclusion of existing policies. (13) Importantly for our study, Yale-NEMS has an established link between the electricity generation and waterborne shipping. While no model is perfect, the NEMS platform is a deeply vetted, comprehensive platform for modeling U.S. energy markets and policies. (14)
Our study has clear policy implications. To date, 16 ports in the United States can supply electricity to vessels at berth. (11) Nevertheless, even in these 16 ports, there is no national requirement that vessels are powered by onshore electricity and, indeed, not all vessels take advantage of the electrification. This state of affairs has contributed to California’s recent “Shore Power Regulation”, which requires 80% of vessel visits to connect to onshore electricity starting in 2020. (15) In addition, while it is unclear whether and when there will be an economy-wide carbon policy in the United States, our analysis is designed to provide insights into the emissions in a future deeper decarbonization scenario of waterborne shipping electrification under carbon pricing.

2. Literature Review

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The reduction of fossil fuel consumption from ports has been of growing interest in recent years. (16−18) To achieve the goal of environmental sustainability, port authorities and policymakers have been implementing technological and organizational innovations, such as optimizing port operations, (19−24) adopting new technologies, (25−27) and using cleaner fuels (i.e., renewable energy, liquefied natural gas, and biofuel). (28−31) There has also been a transition toward the electrification of port activities using onshore grid. (17) Studies have examined the effect of electrifying vessels at berth (also called cold-ironing, alternative marine power, onshore power supply, or shoreside power) on emissions. (32−38) Other diesel-powered port-related cargo handling equipment, e.g., quay cranes, automated guided vehicles (AGVs), and heavy-duty vehicles, can also be electrified to achieve deeper emission reductions. (39−42)
This paper contributes to the literature of waterborne transportation decarbonization. In a related work, Vaishnav et al. (43) use a mixed-integer linear programming model to determine the optimal number of ships and berths to be electrified to maximize net benefits. While Vaishnav et al. provide important insights into the net benefits of near-term relatively modest waterborne shipping electrification policies, our paper differs by examining more intensive electrification policies over a longer time frame (out to the year 2050). Our work is also distinct in that we examine how potential long-term projections of the source of the generation in the electricity grid (both with and without carbon pricing) could influence the net impacts of waterborne shipping electrification going forward, rather than using historical electricity prices and emissions. Earlier studies, such as the 2004 Port of Long Beach study, also provide useful information but are dated and do not attempt to look at the broader implications of electrification. (10)
This paper also contributes to the growing literature harnessing the well-known National Energy Modeling System (NEMS). To date, NEMS (including Yale-NEMS) has been widely used to evaluate energy and environmental policies and market development in the U.S., such as abundant natural gas supply, (44−47) Renewable Portfolio Standards, (48−51) cap and trade and carbon pricing, (52,53) improved energy efficiency, (54−58) and the role of U.S. energy in the global market. (59) To our knowledge, this paper is the first to tackle the electrification of waterborne shipping using a version of NEMS.

3. Methods

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To quantitatively estimate the effects of waterborne shipping electrification on net emissions in the long run, we need a model that simulates waterborne shipping and its interaction with electricity supply. We also require a model that provides the outputs of interest with sufficient spatial granularity. The Yale-NEMS platform is ideally suited to help us answer the research questions. Yale-NEMS is a widely used large-scale general equilibrium model for the U.S. energy system, consisting of all primary demand and supply sectors, such as an electricity market module and a transportation sector module that models waterborne shipping. (44) Yale-NEMS projects energy market equilibrium production, consumption, imports, conversion, and prices from the present to 2050 and incorporates relevant macroeconomic, technology, resource availability, behavior choice, policy, and demographic constraints. The model also projects CO2, SO2, and NOx emissions on the basis of fossil fuel consumption and fuel-specific emissions factors. (60)
An advanced feature of Yale-NEMS is that it provides a reliable framework representing the complex interactions of energy sectors and technological improvement over time in the U.S. energy system. (13) Yale-NEMS also can simulate the market outcomes responding to a wide variety of alternative assumptions and proposed policies. For example, power plants in the electricity market module endogenously select the fuel technologies through cost minimization to generate electricity to meet the demand increase from electrification in the waterborne shipping sector. One limitation of Yale-NEMS is that the electricity market module accounts for detailed factors such as intertemporal operational constraints and interannual variability of renewable resources in a simplified reduced-form manner, following the state-of-the-art for long-run energy system models. This implies that any short-run projections will not be quite as accurate as detailed electricity dispatch models. (61−63) However, our research question focuses on the long run. See the Supporting Information for the modeling details of Yale-NEMS and our post-processing.

3.1. Scenarios

3.1.1. Reference Case

The reference case is based on EIA’s 2017 Annual Energy Outlook (AEO2017). The AEO2017 reference case projects the U.S. energy market and environmental variables out to 2050. The reference case aims to incorporate all current energy and environmental policies at the state and federal levels until their sunset dates, such as the Regional Greenhouse Gas Initiative (RGGI), Cross State Air Pollution Rule (CSAPR), California Assembly Bill 32: California Global Warming Solutions Act of 2006 (AB32), Mercury and Air Toxics Standards (MATS), and Corporate Average Fuel Economy (CAFE) standards set by the Obama Administration. Any rulemakings expired or newly proposed but not yet implemented are not included in the AEO2017 reference case.
There are two published projections in AEO2017. One includes the Clean Power Plan (CPP), and the other excludes it. The CPP was finalized by the Obama Administration in 2015, and it requires states to reduce carbon emissions from the power sector by 32% on average below the 2005 level by 2030. (64) However, the Trump Administration has halted implementation of the CPP and has proposed a replacement rule that most analysts say will lead to few, if any, emission reductions. (65) Thus, we use AEO2017 without the Clean Power Plan as the reference case for this study.
AEO2017 does not project out waterborne electricity consumption, so we create our projections on the basis of historical data of berthed vessels in the U.S. ports. We calculate the amount of electricity from the grid consumed by vessels for each historical year up to 2016 and assume that it scales up on the basis of total energy consumption in all years going forward. We also include any policies that mandate the use of shore power in future years, such as the “California Shore Power Regulation”. To prevent double-counting electricity consumption, we subtract the added electricity used by vessels from commercial electricity demand (see the Supporting Information for the detailed steps).

3.1.2. Electrification Scenarios

We propose three electrification scenarios in this study and are the first to explore the more ambitious second and third scenarios. Because the largest contributor of emissions (e.g., more than 50% of PM2.5 emissions) is directly from ships, (9) we focus on freight and passenger vessel electrification. All types of ports are included in the analysis, including container, bulk, tanker, general cargo, and cruise ship terminals. The first scenario, “Electrifying in Ports”, assumes that, starting from 2019, waterborne vessels replace increasing amounts of their in-port auxiliary engine fuel consumption (e.g., distillate oil, residual oil, and natural gas) with onshore electricity (see the Supporting Information for the linear formula used to switch fossil fuels to electricity). After 2025, vessels replace all in-port auxiliary engine fuel consumption with electricity. The six-year plan we model for implementing waterborne shipping electrification in all U.S. ports would require major policy action but seems plausible on the basis of existing examples. For instance, the construction of facilities for electrifying the Port of San Diego began in mid-2013 and was completed in February 2014. (66) It took five years for the Port of San Francisco to implement shore-side electrification from breaking ground in 2005 to operation in 2010. (67) Our first scenario is the most modest scenario among the three. It follows a trend toward electrification that has already begun, and it allows the vessel main engines to still be reliant on fossil fuels.
Our second scenario is an intermediate case intended to uncover the effects of deeper electrification. This scenario, called “Electrifying in ECA”, electrifies all of the primary and auxiliary fuels that are consumed within the boundary of the North American Emissions Control Area (ECA), which consists of all marine areas within 200 miles of the shoreline where all vessels (both inland and marine) are required to use low-sulfur fuels (0.1% mass starting from January 1, 2015) or invest in abatement technologies. (68) This implies that ports use electric tugboats to take the ships out to the end of the ECA and/or that the vessels can power their main and auxiliary engines using battery electric power for at least some number of miles. As an example, the Port of Auckland in New Zealand is the first port already deploying full-size electric tugboats to maneuver large ships outside the port area so that they do not have to turn on their main engines. (69)
The ECA region is of particular interest to policymakers, as evidenced by the current policy, which requires low-sulfur fuels within this area. However, our results scale with the distance from the port, so these results also provide insight into a scenario where only some fuel use within the ECA is converted to electricity. Just as in the first electrification scenario, we allow the fuel switch to gradually occur, starting from 2019 and increasing to 2025 to make the scenarios comparable. From 2025, distillate oil, residual oil, and natural gas consumption by waterborne shipping are entirely displaced by electricity in this scenario.
The third scenario, “Electrifying All U.S. Fuels”, models the thought experiment of a very ambitious policy that involves dramatic electrification, consistent with deeper decarbonization of shipping. This scenario electrifies all fossil fuels used by the waterborne shipping sector that are attributed to the U.S. energy system, including fuels used to power shipping outside of the 200 mile ECA. This includes all energy consumed or loaded on ships within the borders of the United States. In the scenario, ships would have to entirely electrify the main and auxiliary engines. Thus, there would have to be not only onshore electric facilities and electric tugboats but also large-scale adoption of onboard batteries. This would only be possible with a significant international effort, and thus, we view this scenario as an upper bound on what might be possible. (70) As in the previous scenarios, we model vessels steadily switching to electricity from 2019 to 2025, and starting in 2025, full electrification is achieved. Note that the social benefits associated with electrification in this scenario cannot be entirely attributed to the United States, because the potential emission reduction may occur far away from the U.S. shoreline. However, in all three scenarios, the electricity used by waterborne shipping comes from onshore electricity generation in the United States.

3.1.3. Carbon Pricing Scenarios

We further implement two additional scenarios (“Carbon Pricing” and “Electrifying in ECA and Carbon Pricing”), where a path of gradually increasing carbon prices is imposed on the whole economy. While a future national carbon pricing policy is uncertain, we use this carbon policy and its interaction with electrification as examples that illustrate potential policy implications. Similar to Gillingham and Huang, (44) the carbon price path begins in 2020 at around $2 per metric ton of CO2 in 2016 dollars and ramps up linearly to $46 per metric ton of CO2 in 2040. Subsequently, the price stays constant. As an alternative to the same price for all ports or firms in each year, some countries have implemented or discussed stepwise linear carbon taxation. (71,72) One could see our carbon pricing scheme as the average price across all ports in a region, which would permit stepwise linear taxes implemented at individual ports.
Note that the carbon price trajectory provides an illustrative example of what one modest carbon price path could achieve. Notably, it is below the central case of the social cost of carbon (SCC) estimated by the Obama Administration, (73) but it quickly rises above the estimates of the SCC currently in use by the Trump Administration. (74)

3.2. Monetizing Benefits and Costs

This section illustrates the assumptions for estimating the benefits and costs associated with waterborne shipping electrification. We monetize the social damages caused by pollutant emissions on the basis of the emissions results from Yale-NEMS and estimates of marginal damages from the literature. For CO2 emissions from the waterborne shipping and power generating sectors, we use the central path of the SCC estimates over time, which reflects the Obama Administration’s best effort to develop a set of estimates. (73) Note that this is below the path of carbon prices needed for deeper decarbonization. (75)
For other local air pollutant emissions from the waterborne shipping and power generating sectors, we calculate the total social costs by applying estimates of marginal damages per unit of air pollutant emission from Muller et al. (76) Note that these estimates come with large error bars. (77) The impacts of air pollution in these marginal damage estimates include adverse human health effects, reduced visibility, declined timber and agricultural yields, reductions in recreation services, and increasing material depreciation. We disaggregate the projected Census division-level emissions to the county level based on the EPA National Emission Inventory (NEI) 2014 data and, then, apply them to the county-level marginal estimates to compute the total damages (see Section 2 in Supporting Information for details).
The change in fuel costs incurred by vessels after electrification may be a cost or benefit, depending on the efficiency of each fuel and the relative retail prices of the fuels. Yale-NEMS projects the retail prices for distillate oil, residual oil, natural gas, and electricity. We calculate the total fuel costs of waterborne shipping by multiplying the projected retail fuel prices and consumed quantities.
Electrification also requires retrofitting port berths and vessels, which is a cost in our scenarios. EPA estimates that retrofitting one berth costs $0.5–2.5 million, (11) and we assume that the retrofit cost is $1.5 million/berth, which includes the costs for retrofitting the necessary electrical distribution network. (43) There are 3200 port berths in the U.S. serving deep-draft ships, (78) and we assume that these 3200 berths are steadily electrified from 2019 to 2025, following our scenario designs. We also assume that the operating and maintenance costs per electrified berth are $0.1 million per year. (43)
EPA estimates retrofitting an average vessel will cost around $0.5 million. (11) Of course, vessels are heterogeneous, and some may be much more or less expensive to retrofit; here, we take the average retrofit cost for all vessels. Between July 2013 and December 2014, 3300 vessels were called at U.S. ports. (43) We assume that the total number of vessels increase over the years starting from 2014 at the growth rate of projected waterborne fuel consumption in Yale-NEMS. We then assume the starting number of vessels in 2019 are modified gradually up to 2025, and the vessels newly added to the fleet are modified every year.
In the Electrifying in ECA scenario, the tugboats in place are assumed to be electrified as well. Note that barges are not included in our analysis. We obtained the total number of tugboats registered in the United States from U.S. Army Corps of Engineers (USACE). There were 5809 tug-type workboats operating in the United States in 2017 including both ocean-going and inland boats. Again, we assume that all the tugboats are gradually electrified from 2019 to 2025. Since the actual sale prices for electric tugboats are not publicly available due to confidentiality, we further assume that replacing a traditional diesel-powered tugboat with an electric one costs $2.5 million on average, on the basis of the available evidence. We discuss this evidence and present the details of estimating the cost of replacing a tugboat in the Supporting Information. One caveat of our cost estimate for tugboat replacement is that we do not account for the fact that many of these boats would have been replaced anyway as they aged out of their useful life, and thus, our cost estimate is likely to be an overestimate.

4. Results

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This section presents the primary results for energy consumption, carbon emissions, local air pollutant emissions, and an illustrative cost-benefit analysis across the scenarios.

4.1. Energy Consumption

Figure 1 presents total energy consumption from waterborne shipping over time from different fuels. We see that most energy used by vessels comes from distillate and residual oil in the reference case. There has been a switch in recent decades from residual oil to distillate oil consumption in waterborne shipping, primarily driven by policies, such as Annex VI of the 1997 MARPOL. In all three electrification scenarios (without carbon pricing), from 2019 to 2025, the consumption of fossil fuels is gradually displaced by electricity. The scenarios with carbon pricing lead to substitution from dirty fuels (e.g., residual oil) to cleaner fuels (e.g., natural gas). Figures S2 and S3 present energy consumption shipping type (international and domestic) and port type (seaports and inland ports).

Figure 1

Figure 1. Energy consumption by waterborne shipping in the United States. Note: The carbon price in the carbon pricing scenarios begins in 2020 at approximately $2 per metric ton of CO2 emissions in 2016 U.S. dollars and increases linearly to $46 per metric ton of CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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The electricity consumption by vessels is generated in the power sector from a variety of fuel sources through cost minimization in Yale-NEMS. Figure S4 shows that the increased electricity from waterborne shipping electrification is mainly generated from natural gas and to a lesser extent from renewables and coal.

4.2. Carbon Emissions

Figure 2 presents the net emissions of CO2 in the entire U.S. energy system, both in levels and differences between scenarios. We observe that CO2 emissions in the scenarios without carbon pricing decrease until around 2030 and, then, increase to 2050. This occurs because, around 2030, many of the environmental policies in the U.S. sunset or do not impose further restrictions (e.g., California Global Warming Solutions Act of 2006 and the Regional Greenhouse Gas Initiative). This assumption should not change the relative ordering across the scenarios in the later years, and it is the relative ordering that we care about the most.

Figure 2

Figure 2. Energy-related carbon dioxide emissions for the entire energy system in the United States. Note: The CO2 emission levels are shown in the left panel. The differences in emissions shown in the right panel represent the comparisons of electrification scenarios (with carbon pricing) relative to the reference (with carbon pricing). The carbon price in the carbon pricing scenarios begins in 2020 at approximately $2 per metric ton of CO2 emissions in 2016 U.S. dollars and increases linearly to $46 per metric ton of CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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There are no significant CO2 emission reductions in the three electrification scenarios (without carbon pricing) in the early years, and starting from 2035, CO2 emission reductions increase as the electric grid evolves. In 2050, the decline is 0.05% (2.71 million metric tons (Mt)) in the Electrifying in Ports scenario, 0.3% (16.33 Mt) in the Electrifying in ECA scenario, and 0.4% (21.38 Mt) in the Electrifying All U.S. Fuels scenario compared to the reference case. The CO2 emission reductions are primarily due to increases in coal- and natural gas-generated electricity and the associated transmission losses.
Figure 2 also displays energy-related CO2 net emissions with a carbon pricing policy (dashed lines). Relative to the reference case in 2050, the stand-alone Electrifying in ECA scenario and Carbon Pricing scenario lead to 16.33 and 1021.11 Mt CO2 emission reductions, respectively. However, the combined Electrifying in ECA and Carbon Pricing scenario results in 1071.65 Mt CO2 emission reductions (relative to the reference case), which is larger than the sum of individual policy impacts, or 1037.44 (16.33 + 1021.11) Mt. In addition, the Electrifying in ECA scenario under Carbon Pricing leads to higher CO2 emission reductions (50.54 Mt) than the Electrifying in ECA scenario without Carbon Pricing (16.33 Mt) in 2050. Carbon pricing results in a cleaner fuel source for waterborne shipping electrification, and thus, the combined policies can achieve deeper decarbonization than the sum of the reductions from carbon pricing or electrification run separately. This finding of a complementarity in CO2 emission reductions is useful for policy and only possible because of our integrated modeling approach. Figures S5–S7 present CO2 emissions disaggregated by shipping type, port type, and energy sector (waterborne shipping and electric power).

4.3. Local Air Pollutant Emissions

Figure 3 presents the net emissions of local air pollutants (SO2, NOx, PM2.5, PM10, and VOC). We project these emissions for the waterborne shipping and electricity sectors only (see Section 1.3 in the Supporting Information for the details of the postprocessing approach). Figure 3 shows the drastic decline of local air pollutants (e.g., SO2) in historical years, which was mainly driven by reduced coal-fired electricity generation. For the electrification scenarios without carbon pricing (solid lines), we see significant declines in emissions relative to the reference case because the dirty fuels used by vessels are replaced with electricity generated more efficiently and from cleaner fuels at power plants.

Figure 3

Figure 3. Energy-related local air pollutant emissions for the waterborne shipping and power sectors in the United States. Note: The emissions are from fossil fuel combustions in the waterborne shipping sector (distillate oil, residual oil, and natural gas) and the power sector (coal, oil, and natural gas). Other sources of local air pollutant emissions are not counted. The carbon price begins in 2020 at approximately $2 per metric ton CO2 in 2016 U.S. dollars and increases linearly to $46 per metric ton CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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Relative to the reference case in 2050, Electrifying in Ports leads to about a 8–13% decrease in emissions across the pollutants, Electrifying in the ECA lowers emissions by 50%, and the Electrifying All U.S. Fuels scenario results in up to a 65% decline in local air pollutant emissions. One important caveat is that the results for the Electrifying All U.S. Fuels scenario includes emissions over the oceans, so the emission reductions may not translate directly into improvements in human health to the United States. The carbon pricing scenarios (dashed lines) also show significantly lower local air pollutant emission levels due to the net changes in fossil fuel use, adjusted by the carbon intensity of the fuels.
In contrast to CO2, we do not find a complementarity between carbon pricing and waterborne shipping electrification for local air pollutants. This is primarily because carbon pricing indirectly affects local air pollution through reduced energy use; so, there is less potential for further local air pollution emission reductions from shipping electrification when there is less energy use already in the waterborne shipping sector due to the carbon pricing. Figure S8 presents the comparisons of local air pollutant emissions between scenarios.
Figures S9–S11 also present disaggregated results for local air pollutant emissions. Table S2 shows the comparisons of CO2 and local air pollutant emissions between scenarios in 2050, and Table S3 contains a summary of major results of energy consumption and emissions between the waterborne shipping and power sectors.

4.4. Net Benefits

4.4.1. Illustrative Results of Cost-Benefit Analysis

Table 1 presents the illustrative calculations of the cumulative discounted costs and benefits of the scenarios from 2019 to 2050. All monetary values are in 2016 U.S. dollars. We assume an annual discount rate of 3%. The second column shows the comparison of the Electrification in Ports scenario to the reference case, indicating net benefits of −$2.04 billion. Most of the benefits stem from decreased social costs due to lower air pollutant emissions; however, the benefits are mostly offset by higher electricity prices from electrification (electricity is more expensive than diesel or bunker fuel for shipping). Figure S12 shows the projected electricity prices out to 2050.
Table 1. Cumulative Net Present Values of the Effect of Waterborne Shipping Electrificationa
 Electrifying in Ports vs referenceElectrifying in ECA vs referenceElectrifying in ECA and Carbon Pricing vs Carbon Pricing
fuel costs–53.76–137.56–144.84
port retrofit costs–10.21–10.21–10.21
vessel retrofit costs–2.52–2.52–2.52
social costs of carbon2.5613.2422.43
social costs of local air pollutants61.89252.02248.18
tugboat costs0.00–13.29–13.29
total–2.04101.6799.75
a

All values are in billion 2016 US$. Note: The discount rate is assumed to be 3%. The cash flow includes the years from 2019 to 2050. The carbon tax revenues from the whole economy are not reported. The fuel costs are the product of retail prices and quantities for four fuels, including distillate oil, residual oil, natural gas, and electricity. These results are based on only the shipping and electric sectors; however, inclusion of the other sectors does not appear to change these results in any notable way.

We see considerable positive net benefits of $101.67 billion in the Electrifying in ECA scenario (the third column of Table 1). These positive net benefits stem from reduced social costs of local air pollution despite a substantial increase in fuel costs and the capital/maintenance costs of the electrification. If we simply divide the electrification capital costs by the CO2 emission reductions, we find an average cost of $77 per metric ton CO2 emissions abated, which is less expensive than estimates of the cost needed for deeper decarbonization (e.g., >$100 per metric ton of CO2 emissions estimated in Dietz et al. (75)). The fourth column of Table 1 shows the costs and benefits associated with the Electrifying in ECA combined with Carbon Pricing scenario compared to the Carbon Pricing alone scenario, illustrating the effect of electrification under carbon pricing. The net benefits ($99.75 billion) are still positive but smaller than the net benefits in the third column. This finding is driven by expected higher fuel prices and lower saved social costs of local air pollutant emissions under carbon pricing.
We do not present the net benefits results for the Electrifying All U.S. Fuels scenario, as many of the emission reductions occur far from the coast in the Pacific and Atlantic oceans, and we do not have a sensible way to attribute these to areas in the United States.

4.4.2. Spatial Heterogeneity in Reduced Social Costs of Emissions

Figure 4 shows a map with the changes in cumulative avoided social costs from 2019 to 2050 in the two electrification scenarios compared to the reference case. We see that the social benefits from electrification are primarily clustered in the regions along the coast and inland rivers. The counties that benefit most from waterborne shipping electrification concentrate on the Northeast Coast, Gulf of Mexico, and West Coast. The magnitude of the net benefits depends on where the ships travel, the population of the regions, and the fuels used to generate electricity in these regions (it is not simply a function of the location of the ports). Figure S13 shows that including emissions from power plants does not alter the spatial distribution of social benefits presented in Figure 4. It is out of the scope of this paper to present a detailed cost-benefit analysis for individual ports, but our findings of the spatial effects can be used by specific ports that already have cost numbers in hand.

Figure 4

Figure 4. Cumulative discounted avoided social costs from reduced CO2 and local air pollutant emissions in the waterborne shipping sector. Note: The local air pollutants included in the social cost estimations are SO2, NOx, PM2.5, PM10, and VOC. Carbon costs shown in Table 1 are included as well and assumed to be equally spread across all U.S. counties. The discount rate is assumed to be 3%. The cash flow includes the years from 2019 to 2050. The size of the dots represents the level of avoided social costs, in which the yellow dots indicate the ten counties with the largest values.

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4.5. Sensitivity Analysis

We conduct a series of sensitivity analyses of our baseline results by varying the key assumptions: (1) sensitivity to various electrification ramp-up periods, e.g., 2030 and 2035 (Figures S14 and S15 and Table S4); (2) sensitivity to different assumptions about the value of SCC used in the cost-benefit analysis (Table S5); (3) sensitivity to varying costs of electrification (Table S6); (4) sensitivity to the assumption of cumulating avoided social costs in the U.S. county level (Figure S16); (5) sensitivity to the alternative assumption for estimating CO2 emissions (Figure S17). Our results show that the baseline results are not very sensitive to these alternative assumptions.

5. Discussion

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This paper explores waterborne shipping electrification and how it can interact with an evolving electric grid and a carbon pricing policy. Our results show that electrification can bring about significant net social benefits from curbing local air pollutant emissions and contribute to deeper decarbonization out to 2050. Moreover, we show that electrification along with economy-wide carbon pricing is complementary, leading to greater CO2 emission reductions together than separately (although the opposite is the case for local air pollutants).
There are several caveats worth mentioning. Yale-NEMS does not capture the latest International Maritime Organization (IMO) rule 2020 that sets a 0.5% global sulfur cap for marine fuels (in non-ECA regions) starting from January 1, 2020. (5,79) Second, while we focus on electrifying vessels, other port activities can also be electrified. (39,40) Third, our analysis scope is restricted to ports in the United States (i.e., the fossil fuels and electricity consumption attributed to the U.S. energy system), so transferring our quantitative results to other regions should be treated cautiously. Lastly, we focus on electrification policy and do not compare this policy to other technologies or policies, e.g., scrubbers and mandating ultralow sulfur fuels. (80) Future work could explore optimal policy design among additional available options.
There are important challenges to waterborne electrification. This paper simulates the impact of a hypothetical electrification policy in the United States. To fully implement the policy, the associated technological barriers and requirements must be addressed, such as proper voltage, grid security, and power system reliability. (17,81,82) Thus, significant policy efforts would likely be required to carry out the electrification policy, such as California’s “Shore Power Regulation”, or a government subsidy program. (83) As deeper decarbonization of electricity becomes more likely, future work in this context can shed additional light on how shipping electrification can be a critical puzzle piece in decarbonization efforts.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.0c03298.

  • Text, figures, and tables with detailed information on modeling methods, calculations of emissions and costs, supplemental results, and sensitivity analyses (PDF)

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Acknowledgments

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This publication was developed under Assistance Agreement No. RD835871 awarded by the U.S. Environmental Protection Agency (EPA) to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. We thank Ben Hobbs and Emily Fisher for assistance with the emission factors used for local air pollutant emissions and Paul Kondis, David Daniels, Michael Cole, John Maples, and Erin Boedecker at EIA for their helpful answers to our occasional queries. We also thank the anonymous referees for their constructive comments.

References

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Cited By

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This article is cited by 11 publications.

  1. Jules Wilson, Rupp Carriveau, William Hurley, Reza Babaei, David S-K Ting. Electrifying Maritime Shipping: Evaluating the CO 2 Reduction and Viability of Future Battery-Powered Container Ships Calling at the Port of Los Angeles. Journal of Physics: Conference Series 2024, 2929 (1) , 012007. https://doi.org/10.1088/1742-6596/2929/1/012007
  2. Xu Hao, Deyu Zhou, Ruiheng Zhong, Shunxi Li, Xianming Meng, Bo Liu. Electrification pathways for light-duty logistics vehicles based on perceived cost of ownership in Northern China. Carbon Footprints 2024, 3 (3) https://doi.org/10.20517/cf.2024.24
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  8. Paul Wolfram, Stephanie Weber, Kenneth Gillingham, Edgar G. Hertwich. Pricing indirect emissions accelerates low—carbon transition of US light vehicle sector. Nature Communications 2021, 12 (1) https://doi.org/10.1038/s41467-021-27247-y
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  • Abstract

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    Figure 1

    Figure 1. Energy consumption by waterborne shipping in the United States. Note: The carbon price in the carbon pricing scenarios begins in 2020 at approximately $2 per metric ton of CO2 emissions in 2016 U.S. dollars and increases linearly to $46 per metric ton of CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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    Figure 2

    Figure 2. Energy-related carbon dioxide emissions for the entire energy system in the United States. Note: The CO2 emission levels are shown in the left panel. The differences in emissions shown in the right panel represent the comparisons of electrification scenarios (with carbon pricing) relative to the reference (with carbon pricing). The carbon price in the carbon pricing scenarios begins in 2020 at approximately $2 per metric ton of CO2 emissions in 2016 U.S. dollars and increases linearly to $46 per metric ton of CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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    Figure 3

    Figure 3. Energy-related local air pollutant emissions for the waterborne shipping and power sectors in the United States. Note: The emissions are from fossil fuel combustions in the waterborne shipping sector (distillate oil, residual oil, and natural gas) and the power sector (coal, oil, and natural gas). Other sources of local air pollutant emissions are not counted. The carbon price begins in 2020 at approximately $2 per metric ton CO2 in 2016 U.S. dollars and increases linearly to $46 per metric ton CO2 in 2040. The carbon price remains constant after that. The vertical dotted line separates historical and projected data.

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    Figure 4

    Figure 4. Cumulative discounted avoided social costs from reduced CO2 and local air pollutant emissions in the waterborne shipping sector. Note: The local air pollutants included in the social cost estimations are SO2, NOx, PM2.5, PM10, and VOC. Carbon costs shown in Table 1 are included as well and assumed to be equally spread across all U.S. counties. The discount rate is assumed to be 3%. The cash flow includes the years from 2019 to 2050. The size of the dots represents the level of avoided social costs, in which the yellow dots indicate the ten counties with the largest values.

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      1
      Transport impacts on atmosphere and climate: Shipping
      Eyring, Veronika; Isaksen, Ivar S. A.; Berntsen, Terje; Collins, William J.; Corbett, James J.; Endresen, Oyvind; Grainger, Roy G.; Moldanova, Jana; Schlager, Hans; Stevenson, David S.
      Atmospheric Environment (2010), 44 (37), 4735-4771CODEN: AENVEQ; ISSN:1352-2310. (Elsevier Ltd.)
      Emissions of exhaust gases and particles from oceangoing ships are a significant and growing contributor to the total emissions from the transportation sector. We present an assessment of the contribution of gaseous and particulate emissions from oceangoing shipping to anthropogenic emissions and air quality. We also assess the degrdn. in human health and climate change created by these emissions. Regulating ship emissions requires comprehensive knowledge of current fuel consumption and emissions, understanding of their impact on atm. compn. and climate, and projections of potential future evolutions and mitigation options. Nearly 70% of ship emissions occur within 400 km of coastlines, causing air quality problems through the formation of ground-level ozone, sulfur emissions and particulate matter in coastal areas and harbours with heavy traffic. Furthermore, ozone and aerosol precursor emissions as well as their deriv. species from ships may be transported in the atm. over several hundreds of kilometres, and thus contribute to air quality problems further inland, even though they are emitted at sea. In addn., ship emissions impact climate. Recent studies indicate that the cooling due to altered clouds far outweighs the warming effects from greenhouse gases such as carbon dioxide (CO2) or ozone from shipping, overall causing a neg. present-day radiative forcing (RF). Current efforts to reduce sulfur and other pollutants from shipping may modify this. However, given the short residence time of sulfate compared to CO2, the climate response from sulfate is of the order decades while that of CO2 is centuries. The climatic trade-off between pos. and neg. radiative forcing is still a topic of scientific research, but from what is currently known, a simple cancellation of global mean forcing components is potentially inappropriate and a more comprehensive assessment metric is required. The CO2 equivalent emissions using the global temp. change potential (GTP) metric indicate that after 50 years the net global mean effect of current emissions is close to zero through cancellation of warming by CO2 and cooling by sulfate and nitrogen oxides.
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    2. 2
      Viana, M.; Hammingh, P.; Colette, A.; Querol, X.; Degraeuwe, B.; de Vlieger, I.; van Aardenne, J. Impact of Maritime Transport Emissions on Coastal Air Quality in Europe. Atmos. Environ. 2014, 90, 96– 105,  DOI: 10.1016/j.atmosenv.2014.03.046
      2
      Impact of maritime transport emissions on coastal air quality in Europe
      Viana, Mar; Hammingh, Pieter; Colette, Augustin; Querol, Xavier; Degraeuwe, Bart; de Vlieger, Ina; van Aardenne, John
      Atmospheric Environment (2014), 90 (), 96-105CODEN: AENVEQ; ISSN:1352-2310. (Elsevier Ltd.)
      A review. Shipping emissions are currently increasing and will most likely continue to do so in the future due to the increase of global-scale trade. Ship emissions have the potential to contribute to air quality degrdn. in coastal areas, in addn. to contributing to global air pollution. With the aim to quantify the impacts of shipping emissions on urban air quality in coastal areas in Europe, an in depth literature review was carried out focussing on particulate matter and gaseous pollutants but also reviewing the main chem. tracers of shipping emissions, the particle size distribution of ship-derived particulates and their contributions to population exposure and atm. deposition. Mitigation strategies were also addressed. In European coastal areas, shipping emissions contribute with 1-7% of ambient air PM10 levels, 1-14% of PM2.5, and at least 11% of PM1. Contributions from shipping to ambient NO2 levels range between 7 and 24%, with the highest values being recorded in the Netherlands and Denmark. Impacts from shipping emissions on SO2 concns. were reported for Sweden and Spain. Shipping emissions impact not only the levels and compn. of particulate and gaseous pollutants, but may also enhance new particle formation processes in urban areas.
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    3. 3
      Fu, M.; Liu, H.; Jin, X.; He, K. National- to Port-Level Inventories of Shipping Emissions in China. Environ. Res. Lett. 2017, 12, 114024,  DOI: 10.1088/1748-9326/aa897a
      3
      National- to port-level inventories of shipping emissions in China
      Fu, Mingliang; Liu, Huan; Jin, Xinxin; He, Kebin
      Environmental Research Letters (2017), 12 (11), 114024/1-114024/11CODEN: ERLNAL; ISSN:1748-9326. (IOP Publishing Ltd.)
      Shipping in China plays a global role, and has led worldwide maritime transportation for the last decade. However, without taking national or local port boundaries into account, it is impossible to det. the responsibility that each local authority has on emission controls, nor compare them with land-based emissions to det. the priority for controlling these emissions. In this study, we provide national- to port-level inventories for China. The results show that in 2013, the total emissions of CO, non-methane volatile org. compds.(NMVOCs), nitrogen oxides(NOx), particulate matter(PM), SO2 and CO2 were 0.0741±0.0004 Tg•yr-1, 0.0691±0.0004 Tg•yr-1, 1.91±0.01 Tg•yr-1, 0.164±0.001 Tg•yr-1, 1.30±0.01 Tg•yr-1 and 86.3±0.3 Tg•yr-1 in China, resp. By providing high-resoln. spatial distribution maps of these emissions, we identify three hotspots, centered on the Bohai Rim Area, the Yangtze River Delta and Pearl River Delta. These three hotspots account for 8% of the ocean area evaluated in this study, but contribute around 37% of total shipping emissions. Compared with on-road mobile source emissions, NOx and PM emissions from ships are equiv. to about 34% and 29% of the total mobile vehicle emissions in China. Moreover, this study provides detailed emission inventories for 24 ports in the country, which also greatly contributes to our understanding of global shipping emissions, given that eight of these ports rank within the top twenty of the port league table. Several ports in China suffer emissions 12-147 times higher than those at Los Angeles port. The ports of Ningbo-Zhou Shan, Shanghai, Hong Kong and Dalian dominate the port-level inventories, with individual emissions accounting for 28%-31%, 10%-14%, 10%-12% and 8%-14% of total emissions, resp.
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    4. 4
      Wan, Z.; Zhu, M.; Chen, S.; Sperling, D. Pollution: Three Steps to a Green Shipping Industry. Nature 2016, 530 (7590), 275– 277,  DOI: 10.1038/530275a
      4
      Pollution: Three steps to a green shipping industry
      Wan, Zheng; Zhu, Mo; Chen, Shun; Sperling, Daniel
      Nature (London, United Kingdom) (2016), 530 (7590), 275-277CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      It is time to crack down on pollutant emissions and destructive development caused by vast container vessels which pollute air and seawater. Topics discussed include: pollution problem (NOx, SOx, CO2, particulate matter); and recommendations for green shipping (clean-up ship scrapping, control pollutant emissions, improve port management).
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    5. 5
      Sofiev, M.; Winebrake, J. J.; Johansson, L.; Carr, E. W.; Prank, M.; Soares, J.; Vira, J.; Kouznetsov, R.; Jalkanen, J.-P.; Corbett, J. J. Cleaner Fuels for Ships Provide Public Health Benefits with Climate Tradeoffs. Nat. Commun. 2018, 9 (1), 406,  DOI: 10.1038/s41467-017-02774-9
      5
      Cleaner fuels for ships provide public health benefits with climate tradeoffs
      Sofiev Mikhail; Johansson Lasse; Prank Marje; Soares Joana; Vira Julius; Kouznetsov Rostislav; Jalkanen Jukka-Pekka; Winebrake James J; Carr Edward W; Corbett James J
      Nature communications (2018), 9 (1), 406 ISSN:.
      We evaluate public health and climate impacts of low-sulphur fuels in global shipping. Using high-resolution emissions inventories, integrated atmospheric models, and health risk functions, we assess ship-related PM2.5 pollution impacts in 2020 with and without the use of low-sulphur fuels. Cleaner marine fuels will reduce ship-related premature mortality and morbidity by 34 and 54%, respectively, representing a ~ 2.6% global reduction in PM2.5 cardiovascular and lung cancer deaths and a ~3.6% global reduction in childhood asthma. Despite these reductions, low-sulphur marine fuels will still account for ~250k deaths and ~6.4 M childhood asthma cases annually, and more stringent standards beyond 2020 may provide additional health benefits. Lower sulphur fuels also reduce radiative cooling from ship aerosols by ~80%, equating to a ~3% increase in current estimates of total anthropogenic forcing. Therefore, stronger international shipping policies may need to achieve climate and health targets by jointly reducing greenhouse gases and air pollution.
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    6. 6
      Ring, A. M.; Canty, T. P.; Anderson, D. C.; Vinciguerra, T. P.; He, H.; Goldberg, D. L.; Ehrman, S. H.; Dickerson, R. R.; Salawitch, R. J. Evaluating Commercial Marine Emissions and Their Role in Air Quality Policy Using Observations and the CMAQ Model. Atmos. Environ. 2018, 173, 96– 107,  DOI: 10.1016/j.atmosenv.2017.10.037
      6
      Evaluating commercial marine emissions and their role in air quality policy using observations and the CMAQ model
      Ring, Allison M.; Canty, Timothy P.; Anderson, Daniel C.; Vinciguerra, Timothy P.; He, Hao; Goldberg, Daniel L.; Ehrman, Sheryl H.; Dickerson, Russell R.; Salawitch, Ross J.
      Atmospheric Environment (2018), 173 (), 96-107CODEN: AENVEQ; ISSN:1352-2310. (Elsevier Ltd.)
      We investigate the representation of emissions from the largest (Class 3) com. marine vessels (c3 Marine) within the Community Multiscale Air Quality (CMAQ) model. In present emissions inventories developed by the United States Environmental Protection Agency (EPA), c3 Marine emissions are divided into off-shore and near-shore files. Off-shore c3 Marine emissions are vertically distributed within the atm. column, reflecting stack-height and plume rise. Near-shore c3 Marine emissions, located close to the US shoreline, are erroneously assumed to occur only at the surface. We adjust the near-shore c3 Marine emissions inventory by vertically distributing these emissions to be consistent with the off-shore c3 Marine inventory. Addnl., we remove near-shore c3 Marine emissions that overlap with off-shore c3 Marine emissions within the EPA files. The CMAQ model generally overestimates surface ozone (O3) compared to Air Quality System (AQS) site observations, with the largest discrepancies occurring near coastal waterways. We compare modeled O3 from two CMAQ simulations for June, July, and August (JJA) 2011 to surface O3 observations from AQS sites to examine the efficacy of the c3 Marine emissions improvements. Model results at AQS sites show av. max. 8-h surface O3 decreases up to ∼6.5 ppb along the Chesapeake Bay, and increases ∼3-4 ppb around Long Island Sound, when the adjusted c3 Marine emissions are used. Along with the c3 Marine emissions adjustments, we reduce on-road mobile NOX emissions by 50%, motivated by work from Anderson et al. 2014, and reduce the lifetime of the alkyl nitrate species group from ∼10 days to ∼1 day based on work by Canty et al. 2015, to develop the "c3 Science" model scenario. Simulations with these adjustments further improve model representation of the atm. We calc. the ratio of column formaldehyde (HCHO) and tropospheric column nitrogen dioxide (NO2) using observations from the Ozone Monitoring Instrument and CMAQ model output to investigate the photochem. O3 prodn. regime (VOC or NOX-limited) of the obsd. and modeled atm. Compared to the baseline, the c3 Science model scenario more closely simulates the HCHO/NO2 ratio calcd. from OMI data. Model simulations for JJA 2018 using the c3 Science scenario show a redn. of surface O3 by as much as ∼13 ppb for areas around the Chesapeake Bay and ∼2-3 ppb at locations in NY and CT downwind of New York City. These redns. are larger in 2018 than in 2011 due to a change in the photochem. O3 prodn. regime in the Long Island Sound region and the projected decline of other (non-c3 Marine) sources of O3 precursors, highlighting the importance of proper representation of c3 Marine emissions in future modeling scenarios.
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    7. 7
      Corbett, J. J.; Winebrake, J. J.; Green, E. H.; Kasibhatla, P.; Eyring, V.; Lauer, A. Mortality from Ship Emissions: A Global Assessment. Environ. Sci. Technol. 2007, 41 (24), 8512– 8518,  DOI: 10.1021/es071686z
      7
      Mortality from Ship Emissions: A Global Assessment
      Corbett, James J.; Winebrake, James J.; Green, Erin H.; Kasibhatla, Prasad; Eyring, Veronika; Lauer, Axel
      Environmental Science & Technology (2007), 41 (24), 8512-8518CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
      Epidemiol. studies consistently link ambient particulate matter (PM) concns. to neg. health impacts, including asthma, heart attack, hospital admission, and premature mortality. The authors modeled ambient PM concns. from ocean-going ships using 2 geo-spatial emissions inventories and 2 global aerosol models. Global and regional mortalities were estd. by applying ambient PM increases due to ship emissions to cardiopulmonary and lung cancer concn.-risk functions and population models. Results indicated shipping-related PM emissions are responsible for ∼60,000 cardiopulmonary and lung cancer deaths annually; most deaths occurred near coastlines in Europe and East and South Asia. Under current regulation and with the expected growth in shipping activity, the authors est. annual mortalities could increase by 40% by 2012.
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    8. 8
      EPA. Third Report to Congress: Highlights from the Diesel Emissions Reduction Program; EPA: Washington, DC, 2016.
      There is no corresponding record for this reference.
    9. 9
      EPA. National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gses at U.S. Ports; EPA: Washington, DC, 2016.
      There is no corresponding record for this reference.
    10. 10
      ENVIRON. Cold Ironing Cost Effectiveness Study; ENVIRON International Corporation: Los Angeles, CA, 2004.
      There is no corresponding record for this reference.
    11. 11
      EPA. Shore Power Technology Assessment at U.S. Ports; EPA: Washington, DC, 2017.
      There is no corresponding record for this reference.
    12. 12
      Fernández Astudillo, M.; Vaillancourt, K.; Pineau, P. O.; Amor, B. Human Health and Ecosystem Impacts of Deep Decarbonization of the Energy System. Environ. Sci. Technol. 2019, 53, 14054– 14062,  DOI: 10.1021/acs.est.9b04923
      12
      Human Health and Ecosystem Impacts of Deep Decarbonization of the Energy System
      Fernandez Astudillo, Miguel; Vaillancourt, Kathleen; Pineau, Pierre-Olivier; Amor, Ben
      Environmental Science & Technology (2019), 53 (23), 14054-14062CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
      Global warming mitigation strategies are likely to affect human health and biodiversity via diverse cause-effect mechanisms. To analyze these effects, a method linking TIMES (the integrated Markal-Efom system) energy models with life cycle assessment using open-source software was implemented. This proposed method uses a cut-off to identify the most relevant processes. These processes had their efficiencies, fuel mixes, and emission factors updated to be consistent with the TIMES model. Using a cut-off criterion exponentially reduced the no. of connection points between models and facilitated scenario analyses with a large no. of technologies involved. This method assessed the potential effects of deploying low-C technologies to reduce combustion emissions in Quebec Province, Canada. The redn. of combustion emissions was largely achieved by energy services electrification. Global warming mitigation efforts reduced human health and ecosystem quality impacts, mainly because of lower global warming, water scarcity, and metal contamination impacts. The TIMES model alone underestimated the redn. of CO2 equiv. 21% with respect to a full account of emissions.
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    13. 13
      EIA. The National Energy Modeling System: An Overview 2009; EIA: Washington, DC, 2009.
      There is no corresponding record for this reference.
    14. 14
      Winebrake, J. J.; Sakva, D. An Evaluation of Errors in US Energy Forecasts: 1982–2003. Energy Policy 2006, 34 (18), 3475– 3483,  DOI: 10.1016/j.enpol.2005.07.018
      There is no corresponding record for this reference.
    15. 15
      California Air Resources Board. Shore Power for Ocean-Going Vessels; https://ww2.arb.ca.gov/our-work/programs/ocean-going-vessels-berth-regulation (accessed 2020-04-24).
      There is no corresponding record for this reference.
    16. 16
      Acciaro, M.; Vanelslander, T.; Sys, C.; Ferrari, C.; Roumboutsos, A.; Giuliano, G.; Lam, J. S. L.; Kapros, S. Environmental Sustainability in Seaports: A Framework for Successful Innovation. Marit. Policy Manag. 2014, 41 (5), 480– 500,  DOI: 10.1080/03088839.2014.932926
      There is no corresponding record for this reference.
    17. 17
      Iris, Ç.; Lam, J. S. L. A Review of Energy Efficiency in Ports: Operational Strategies, Technologies and Energy Management Systems. Renewable Sustainable Energy Rev. 2019, 112, 170– 182,  DOI: 10.1016/j.rser.2019.04.069
      There is no corresponding record for this reference.
    18. 18
      Bouman, E. A.; Lindstad, E.; Rialland, A. I.; Strømman, A. H. State-of-the-Art Technologies, Measures, and Potential for Reducing GHG Emissions from Shipping – A Review. Transp. Res. Part D Transp. Environ. 2017, 52, 408– 421,  DOI: 10.1016/j.trd.2017.03.022
      There is no corresponding record for this reference.
    19. 19
      Du, Y.; Chen, Q.; Quan, X.; Long, L.; Fung, R. Y. K. Berth Allocation Considering Fuel Consumption and Vessel Emissions. Transp. Res. Part E Logist. Transp. Rev. 2011, 47 (6), 1021– 1037,  DOI: 10.1016/j.tre.2011.05.011
      There is no corresponding record for this reference.
    20. 20
      Venturini, G.; Iris, Ç.; Kontovas, C. A.; Larsen, A. The Multi-Port Berth Allocation Problem with Speed Optimization and Emission Considerations. Transp. Res. Part D Transp. Environ. 2017, 54, 142– 159,  DOI: 10.1016/j.trd.2017.05.002
      There is no corresponding record for this reference.
    21. 21
      Iris, Ç.; Pacino, D.; Ropke, S.; Larsen, A. Integrated Berth Allocation and Quay Crane Assignment Problem: Set Partitioning Models and Computational Results. Transp. Res. Part E Logist. Transp. Rev. 2015, 81, 75– 97,  DOI: 10.1016/j.tre.2015.06.008
      There is no corresponding record for this reference.
    22. 22
      Davarzani, H.; Fahimnia, B.; Bell, M.; Sarkis, J. Greening Ports and Maritime Logistics: A Review. Transp. Res. Part D Transp. Environ. 2016, 48, 473– 487,  DOI: 10.1016/j.trd.2015.07.007
      There is no corresponding record for this reference.
    23. 23
      Johnson, H.; Styhre, L. Increased Energy Efficiency in Short Sea Shipping through Decreased Time in Port. Transp. Res. Part A Policy Pract. 2015, 71, 167– 178,  DOI: 10.1016/j.tra.2014.11.008
      There is no corresponding record for this reference.
    24. 24
      Buhrkal, K.; Zuglian, S.; Ropke, S.; Larsen, J.; Lusby, R. Models for the Discrete Berth Allocation Problem: A Computational Comparison. Transp. Res. Part E Logist. Transp. Rev. 2011, 47 (4), 461– 473,  DOI: 10.1016/j.tre.2010.11.016
      There is no corresponding record for this reference.
    25. 25
      Zis, T.; North, R. J.; Angeloudis, P.; Ochieng, W. Y.; Bell, M. G. H. Evaluation of Cold Ironing and Speed Reduction Policies to Reduce Ship Emissions near and at Ports. Marit. Econ. Logist. 2014, 16 (4), 371– 398,  DOI: 10.1057/mel.2014.6
      There is no corresponding record for this reference.
    26. 26
      Antonelli, M.; Ceraolo, M.; Desideri, U.; Lutzemberger, G.; Sani, L. Hybridization of Rubber Tired Gantry (RTG) Cranes. J. Energy Storage 2017, 12, 186– 195,  DOI: 10.1016/j.est.2017.05.004
      There is no corresponding record for this reference.
    27. 27
      Bolonne, S. R. A.; Chandima, D. P. Sizing an Energy System for Hybrid Li-Ion Battery-Supercapacitor RTG Cranes Based on State Machine Energy Controller. IEEE Access 2019, 7, 71209– 71220,  DOI: 10.1109/ACCESS.2019.2919345
      There is no corresponding record for this reference.
    28. 28
      Bengtsson, S.; Andersson, K.; Fridell, E. A Comparative Life Cycle Assessment of Marine Fuels: Liquefied Natural Gas and Three Other Fossil Fuels. Proc. Inst. Mech. Eng. Part M J. Eng. Marit. Environ. 2011, 225 (2), 97– 110,  DOI: 10.1177/1475090211402136
      There is no corresponding record for this reference.
    29. 29
      Geerlings, H.; Van Duin, R. A New Method for Assessing CO2-Emissions from Container Terminals: A Promising Approach Applied in Rotterdam. J. Cleaner Prod. 2011, 19 (6–7), 657– 666,  DOI: 10.1016/j.jclepro.2010.10.012
      There is no corresponding record for this reference.
    30. 30
      Acciaro, M.; Ghiara, H.; Cusano, M. I. Energy Management in Seaports: A New Role for Port Authorities. Energy Policy 2014, 71, 4– 12,  DOI: 10.1016/j.enpol.2014.04.013
      There is no corresponding record for this reference.
    31. 31
      Boile, M.; Theofanis, S.; Sdoukopoulos, E.; Plytas, N. Developing a Port Energy Management Plan: Issues, Challenges, and Prospects. Transp. Res. Rec. 2016, 2549, 19– 28,  DOI: 10.3141/2549-03
      There is no corresponding record for this reference.
    32. 32
      Sciberras, E. A.; Zahawi, B.; Atkinson, D. J. Electrical Characteristics of Cold Ironing Energy Supply for Berthed Ships. Transp. Res. Part D Transp. Environ. 2015, 39, 31– 43,  DOI: 10.1016/j.trd.2015.05.007
      There is no corresponding record for this reference.
    33. 33
      Hall, W. J. Assessment of CO2 and Priority Pollutant Reduction by Installation of Shoreside Power. Resour. Conserv. Recycl. 2010, 54 (7), 462– 467,  DOI: 10.1016/j.resconrec.2009.10.002
      There is no corresponding record for this reference.
    34. 34
      Ballini, F.; Bozzo, R. Air Pollution from Ships in Ports: The Socio-Economic Benefit of Cold-Ironing Technology. Res. Transp. Bus. Manag. 2015, 17, 92– 98,  DOI: 10.1016/j.rtbm.2015.10.007
      There is no corresponding record for this reference.
    35. 35
      Chang, C. C.; Wang, C. M. Evaluating the Effects of Green Port Policy: Case Study of Kaohsiung Harbor in Taiwan. Transp. Res. Part D Transp. Environ. 2012, 17 (3), 185– 189,  DOI: 10.1016/j.trd.2011.11.006
      There is no corresponding record for this reference.
    36. 36
      Tsekouras, G. J.; Kanellos, F. D. Ship to Shore Connection – Reliability Analysis of Ship Power System. In Proceedings - 2016 22nd International Conference on Electrical Machines, ICEM 2016; Institute of Electrical and Electronics Engineers Inc., 2016; pp 2955– 2961; DOI: 10.1109/ICELMACH.2016.7732944 .
      There is no corresponding record for this reference.
    37. 37
      Yiğit, K.; Kökkülünk, G.; Parlak, A.; Karakaş, A. Energy Cost Assessment of Shoreside Power Supply Considering the Smart Grid Concept: A Case Study for a Bulk Carrier Ship. Marit. Policy Manag. 2016, 43 (4), 469– 482,  DOI: 10.1080/03088839.2015.1129674
      There is no corresponding record for this reference.
    38. 38
      Coppola, T.; Fantauzzi, M.; Miranda, S.; Quaranta, F. Cost/Benefit Analysis of Alternative Systems for Feeding Electric Energy to Ships in Port from Ashore. In AEIT 2016 - International Annual Conference: Sustainable Development in the Mediterranean Area, Energy and ICT Networks of the Future; Institute of Electrical and Electronics Engineers Inc., 2016; DOI: 10.23919/AEIT.2016.7892782 .
      There is no corresponding record for this reference.
    39. 39
      Schmidt, J.; Meyer-Barlag, C.; Eisel, M.; Kolbe, L. M.; Appelrath, H. J. Using Battery-Electric AGVs in Container Terminals - Assessing the Potential and Optimizing the Economic Viability. Res. Transp. Bus. Manag. 2015, 17, 99– 111,  DOI: 10.1016/j.rtbm.2015.09.002
      There is no corresponding record for this reference.
    40. 40
      Yang, Y. C.; Chang, W. M. Impacts of Electric Rubber-Tired Gantries on Green Port Performance. Res. Transp. Bus. Manag. 2013, 8, 67– 76,  DOI: 10.1016/j.rtbm.2013.04.002
      There is no corresponding record for this reference.
    41. 41
      Yang, Y. C.; Lin, C. L. Performance Analysis of Cargo-Handling Equipment from a Green Container Terminal Perspective. Transp. Res. Part D Transp. Environ. 2013, 23, 9– 11,  DOI: 10.1016/j.trd.2013.03.009
      There is no corresponding record for this reference.
    42. 42
      van Duin, J. H. R.; Geerlings, H.; Verbraeck, A.; Nafde, T. Cooling down: A Simulation Approach to Reduce Energy Peaks of Reefers at Terminals. J. Cleaner Prod. 2018, 193, 72– 86,  DOI: 10.1016/j.jclepro.2018.04.258
      There is no corresponding record for this reference.
    43. 43
      Vaishnav, P.; Fischbeck, P. S.; Morgan, M. G.; Corbett, J. J. Shore Power for Vessels Calling at U.S. Ports: Benefits and Costs. Environ. Sci. Technol. 2016, 50 (3), 1102– 1110,  DOI: 10.1021/acs.est.5b04860
      43
      Shore Power for Vessels Calling at U.S. Ports: Benefits and Costs
      Vaishnav, Parth; Fischbeck, Paul S.; Morgan, M. Granger; Corbett, James J.
      Environmental Science & Technology (2016), 50 (3), 1102-1110CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
      When in port, ships burn marine diesel in on-board generators to produce electricity and are significant contributors to poor local and regional air quality. Supplying ships with grid electricity can reduce these emissions. This work used 2 integrated assessment models to quantify benefits of reducing NOx, SO2, PM2.5, and CO2 emissions by ships using shore power. With historical vessel call data, combinations of vessels and berths at US ports were identified which could be switched to shore power to yield the largest societal gains. Results indicated that, depending on assumed social pollution costs, an air quality benefit of $70-150 million/yr could be achieved by retrofitting 1/4 to 2/3 of all vessels which call at US ports. Such a benefit could be produced at no net cost to society (health and environmental benefits are balanced by the cost of ship and port retrofit), but would require many ships to be equipped to receive shore power, even if doing so resulted in a private loss for the operator. Policy-makers could produce a net societal gain by implementing incentives and mandates to encourage a shift toward shore power.
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      Kotzur, L.; Markewitz, P.; Robinius, M.; Stolten, D. Impact of Different Time Series Aggregation Methods on Optimal Energy System Design. Renewable Energy 2018, 117, 474– 487,  DOI: 10.1016/j.renene.2017.10.017
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      EPA. Overview of the Clean Power Plan: Cutting Carbon Pollution from Power Plants; EPA: Washington, DC, 2015.
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      Keyes, A. T.; Lambert, K. F.; Burtraw, D.; Buonocore, J. J.; Levy, J. I.; Driscoll, C. T. The Affordable Clean Energy Rule and the Impact of Emissions Rebound on Carbon Dioxide and Criteria Air Pollutant Emissions. Environ. Res. Lett. 2019, 14 (4), 044018  DOI: 10.1088/1748-9326/aafe25
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      The Affordable Clean Energy rule and the impact of emissions rebound on carbon dioxide and criteria air pollutant emissions
      Keyes, Amelia T.; Lambert, Kathleen F.; Burtraw, Dallas; Buonocore, Jonathan J.; Levy, Jonathan I.; Driscoll, Charles T.
      Environmental Research Letters (2019), 14 (4), 44018CODEN: ERLNAL; ISSN:1748-9326. (IOP Publishing Ltd.)
      TheAffordableClean Energy (ACE) rule, theUSEnvironmental ProtectionAgency's (EPA) proposed replacement of the Clean Power Plan (CPP), targets heat rate improvements (HRIs) at individual coal plants in theUS. Due to greater plant efficiency, suchHRIs could lead to increased generation and emissions, known as an emissions rebound effect.The EPA Regulatory Impact Anal. for theACEand other analyses to date have not quantified themagnitude and extent of an emissions rebound.Weanalyze the estd. emissions rebound of carbon dioxide (CO2) and criteria pollutants sulfur dioxide (SO2) and nitrogen oxides (NOX), using results from theEPA's power sector model, under theACEin 2030 at model coal plants and at the state and national levels compared to both no policy and theCPP.We decomp. emissions changes under a central illustrativeACEscenario and find evidence of a state-level rebound effect.Although theACEreduces the emissions intensity of coal plants, it is expected to increase the no. of operating coal plants and amt. of coal-fired electricity generation, with28%of model plants showing higherCO2 emissions in 2030 compared to no policy. As a result, theACEonlymodestly reduces national power sectorCO2 emissions and increasesCO2 emissions by up to 8.7%in 18 states plus the District of Columbia in 2030 compared to no policy.We also find that theACEincreases SO2 andNOX emissions in 19 states and 20 states plus DC, resp., in 2030 compared to no policy,with implications for air quality and public health.We compare our findings to othermodel years, addnl. EPAACE scenarios, and other modeling results for similar policies, finding similar outcomes. Our results demonstrate the importance of considering the emissions rebound effect and its effect on sub-national emissionsoutcomes inevaluating theACE and similar policies targeting HRIs.
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      SAFETY4SEA. Port of San Diego celebrates shore power installation; https://safety4sea.com/port-of-san-diego-celebrates-shore-power-installation-2/ (accessed 2019-11-27).
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      Port of San Francisco. Mayor and Port of SF inaugurate Cruise Ship using Shoreside Power; https://sfport.com/article/mayor-and-port-sf-inaugurate-cruise-ship-using-shoreside-power (accessed 2019-11-27).
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      Carr, E. W.; Corbett, J. J. Ship Compliance in Emission Control Areas: Technology Costs and Policy Instruments. Environ. Sci. Technol. 2015, 49 (16), 9584– 9591,  DOI: 10.1021/acs.est.5b02151
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      Ship Compliance in Emission Control Areas: Technology Costs and Policy Instruments
      Carr, Edward W.; Corbett, James J.
      Environmental Science & Technology (2015), 49 (16), 9584-9591CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
      This work assessed whether a Panama Canal Authority pollution tax is an effective economic instrument to achieve emission control area (ECA)-like redns. in emissions from ships transiting the Panama Canal. This tariff-based policy action, where vessels in compliance with International Maritime Organization (IMO) ECA stds. pay a lower transit tariff than non-compliant vessels, may be a feasible alternative to petition for a Panamanian ECA through the IMO. A $4.06/container fuel tax could incentivize ECA-compliant emissions redns. for nearly 2/3 of Panama Canal container vessels, mainly by fuel switching; if the vessel(s) also operate in IMO-defined ECA, exhaust gas treatment technologies may be cost-effective. The presented RATES (regional assessment of technol., tolls, and emissions from ships) model compared current abatement technologies based on hours of operation within an ECA, computing costs for a container vessel to comply with ECA stds. in addn. to computing the Canal tax which would reduce emissions in Panama. Retrofitted open-loop scrubbers are cost-effective only for vessels operating within an ECA for >4500 h annually. Fuel switching is the least-cost option to industry for vessels operating mostly outside ECA regions; vessels operating entirely within an ECA region could reduce compliance costs with exhaust gas treatment technol. (scrubbers).
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      Ports of Auckland. Ports of Auckland buys world first electric tug; http://www.poal.co.nz/media/ports-of-auckland-buys-world-first-electric-tug (accessed 2019-11-27).
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      Filks, I. Batteries included: Sweden’s emissions-free ferries lead the charge; https://www.reuters.com/article/us-denmark-battery-ferry/batteries-included-swedens-emissions-free-ferries-lead-the-charge-idUSKCN1QV1W7 (accessed 2019-11-27).
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      Wang, T.; Wang, X.; Meng, Q. Joint Berth Allocation and Quay Crane Assignment under Different Carbon Taxation Policies. Transp. Res. Part B Methodol. 2018, 117, 18– 36,  DOI: 10.1016/j.trb.2018.08.012
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      Health co-benefits of sub-national renewable energy policy in the US
      Dimanchev, Emil G.; Paltsev, Sergey; Yuan, Mei; Rothenberg, Daniel; Tessum, Christopher W.; Marshall, Julian D.; Selin, Noelle E.
      Environmental Research Letters (2019), 14 (8), 085012CODEN: ERLNAL; ISSN:1748-9326. (IOP Publishing Ltd.)
      State and local policy-makers in the US have shown interest in transitioning electricity systems toward renewable energy sources and in mitigating harmful air pollution. However, the extent to which sub-national renewable energy policies can improve air quality remains unclear. To investigate this issue, we develop a systemic modeling framework that combines economic and air pollution models to assess the projected sub-national impacts of Renewable Portfolio Stds. (RPSs) on air quality and human health, as well as on the economy and on climate change. We contribute to existing RPS cost-benefit literature by providing a comprehensive assessment of economic costs and estg. economy-wide changes in emissions and their impacts, using a general equil. modeling approach. This study is also the first to our knowledge to directly compare the health co-benefits of RPSs to those of carbon pricing. We est. that existing RPSs in the 'Rust Belt' region generate a health co-benefit of $94 per ton CO2 reduced ($2-477/tCO2) in 2030, or 8¢ for each kWh of renewable energy deployed (0.2-40¢ kWh-1) in 2015 dollars. Our central est. is 34% larger than total policy costs. We est. that the central marginal benefit of raising renewable energy requirements exceeds the marginal cost, suggesting that strengthening RPSs increases net societal benefits. We also calc. that carbon pricing delivers health co-benefits of $211/tCO2 in 2030, 63% greater than the health co-benefit of reducing the same amt. of CO2 through an RPS approach.
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      Wu, L.; Wang, S. The Shore Power Deployment Problem for Maritime Transportation. Transp. Res. Part E Logist. Transp. Rev. 2020, 135, 101883,  DOI: 10.1016/j.tre.2020.101883
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