Energy-Water-CO2 Nexus of Fossil Fuel Based Power Generation

Kyuha Lee and Bhavik R Bakshi*

Introduction

Thermoelectric power plants generate electricity and flue gas scrubbers mitigate emissions from the plants. However, at the same time, these plants withdraw large quantities of water from the watershed. In the United States, this withdrawal corresponds to 45% of the total 2010 water use (Maupin et al., 2014). In addition, NOv emissions from the scrubbers cause deposition of excessive nutrients in the watershed. Therefore, increasing electricity generation could increase water stress, deteriorate water quality, and contribute to climate change. Also, in the watershed where power plants are located, other activities, such as fanning, interact with the power plants since these activities also require water from the watershed as well as energy from the power plants and release nutrients to the watershed. To prevent shifting of environmental impacts across multiple flows (Bakshi et al.. 2018), the energy-water nexus between different activities in the watershed needs to be understood in assessing the impacts of power plants and sustainability of the watershed (Sanders, 2014).

Fossil fuel power plants not only require a huge amount of water, but also emit 28% of the 2016 U.S. greenhouse gas emissions (EPA, 2018a), 67% of the 2014 U.S. SO, emissions, and 12% of the 2014 U.S. NOy emissions (EPA, 2014). Ecosystem sendees, such as climate change regulation and air quality regulation, could play an important role in mitigating these pollutants and emissions. The ecosystem provides many essential goods and sendees to society and for our well-being. Ecosystem goods include water and fossil resources that our society has been extensively utilizing. Ecosystem sendees include air and water quality regulation and carbon sequestration by soil and vegetation. Therefore, in addition to the conventional energy-water nexus concept, we need to expand the system boundary to include the role of ecosystems. The framework of Techno-Ecological Synergy (TES) has been developed to account for the role of ecosystems in engineering and other human activities (Bakshi et al., 2015; Gopalakidslman et al., 2016). In this framework, the demand for ecosystem sendees imposed by human activities, which correspond to the emissions and resource use, must not exceed the capacity of the corresponding ecosystem to supply the demanded goods and sendees. This condition needs to be satisfied in order to claim environmental sustainability of any activity. For example, for environmental sustainability of a power plant in a watershed, the amount of water consumed by the power plant should be smaller than the amount of renewable water available to the plant from the watershed. Otherwise, power plants will likely fail at some point because water resource will become scarce.

In the watershed where power plants are located, other activities, such as residential, industrial, and fanning, also share the supply of ecosystem goods and sendees with electricity generation activity. Also, to address watershed-scale sustainability, the demand for ecosystem sendees from all activities in a watershed needs to be considered. This raises the need for a holistic assessment to investigate watershed sustainability. In such an analysis, the trade-offs between multiple objectives, such as water quality, water quantity, net electricity generation, climate change, and air quality objectives, could be identified as well.

In this work, we employ a holistic analysis approach to investigate the energy-water-СО, nexus for thermoelectric power plants, with specific focus on the Muskingum River Watershed (MRW) in Ohio in the United States. In 2014, two coal-fired power plants and three NG-fired power plants were located in the MRW. The year 2014 is selected because of data availability from a variety of online sources and reports. The holistic analysis boundary includes thermoelectric power generation, mining, residential, commercial, industrial, agricultural, transportation and wastewater treatment activities.

To suggest a better recommendation for sustainable watershed management, various alternatives for both technological and agroecological activities are considered. Technological alternatives include fuel mining and cooling technology options for power generation, CO, conversion options, and renewable power generation options. Agroecological alternatives include tillage practice options and land use change options. Scenarios for each alternative are analyzed in order to understand the trade-offs between multiple flows.

CO, flows are affected by both technological and agroecological alternatives in various ways. Technological alternatives mainly aim to reduce CO, emissions, while agroecological alternatives improve carbon sequestration in soil and vegetation. Broader implications in terms of CO, management are addressed through the holistic analysis of watershed activities.

The goal of this work consists of three pails. First, we identify ecological overshoots for activities in the MRW. Second, we investigate various alternative scenarios in order to understand the trade-offs between energy, water, and CO, flows. Third, we suggest better watershed management solutions that could be “win-win” in terms of multiple objectives for watershed sustainability.

Watershed Activities

In this section, we describe the characteristics of various watershed activities that are included in this holistic assessment study. Data collection is a challenging task for such a holistic assessment because we need to rely on multiple data sources that often have different spatial and temporal data resolutions. Thus, it is important to keep spatial and temporal consistency between data. In this study, watershed- scale data for the year 2014 is preferred because most data are available for this year. The watershed boundary is determined by the Hydrologic Unit Code (HUC) system that assigns a unique HUC code to each watershed (Seaber et al., 1987). Each HUC region is defined by distinct hydrologic features, such as rivers, lakes, and drainage basins. The Muskingum River Watershed (MRW) studied in this work corresponds to a region where 8-digits of HUC (HUC8) is assigned as 05040004. The MRW is located in southeast Ohio. Water flows from the MRW drains into the Muskingum River, which eventually flows into the Ohio River. Figure 1 shows laud use and laud cover features in the MRW.

If any data are not available for HUC8 spatial resolution, the data is allocated to HUC8 based on the ratio of population or area. For example, data for air pollutants is available for U.S. counties (EPA, 2014), which do not match HUC spatial resolution. The MRW includes eight comities in Ohio: Coshocton, Licking, Knox, Muskingum. Репу, Morgan, Washington, and Noble. The county-level data are then allocated to the MRW, based on the ratio of HUC8 area to eight comities’ area. For other data, such as residential and commercial activity data, that are more dependent on population rather than area, the allocation is performed based on the population. Table 1 summarizes data inventories, data sources, and spatial data resolution for this work. When life cycle inventory databases, such as GREET (Wang. 2016) and USLCI (NREL, 2018), are used to obtain data, only on-site data are collected since the scope of this study is limited to the watershed scale. Figure 2 represents the scope of this study that includes various watershed activities and resource, waste, and ecosystem flows. In the following sections, we pror ide brief descriptions of each watershed activity.

Land use and land cover features in the Muskingum River Watershed (HUC8

Figure 1. Land use and land cover features in the Muskingum River Watershed (HUC8: 05000405) in Ohio. Five thermoelectric powerplants (#) were located in the MRWin 2014.

Scope of this study that includes various watershed activities and resource, waste, and ecosystem flows. Food production flow from agricultural activity is excluded from this study

Figure 2. Scope of this study that includes various watershed activities and resource, waste, and ecosystem flows. Food production flow from agricultural activity is excluded from this study.

Table 1. Data sources for activities and envnonmental interventions in the MRW. If the spatial resolution of data is larger than HUC8 scale, the data is allocated to the HUC8 scale based on the ratio of population or area.

Activity

Environmental & material flow

Data source

Spatial resolution

Theremoelectric

GHG emissions

EPAeGRID (EPA, 2016)

Facility

An pollutants

EPANEI (EPA, 2014)

County

Water pollutants

EPANPDES (Ohio EPA, 2018)

Facility

Thermal water pollution

EIA-923 (EIA, 2018a)

Facility

Water withdrawal

ELA-923 (EIA, 2018a)

Facility

Water consumption

EIA-923 (EIA, 2018a)

Facility

Natural gas use

EIA-923 (EIA, 2018a)

Facility

Electricity use

EIA-923 (EIA, 2018a)

Facility

Electricity generation

EIA-923 (EIA, 2018a)

Facility

Mining

GHG emissions

GREET (Wang, 2016)

U.S.average

An pollutants

EPANEI (EPA 2014)

County

Water pollutants

NETL (Skone, 2016; Skone et al., 2016)

Appalachia average

Water withdrawal

USGS (Solley et al., 1998)

Ohio

Water consumption

GREET (Wang, 2016)

U.S.average

Natural gas use

EIA (EIA, 2018b)

Ohio

Electricity use

USLCI (NREL, 2018)

U.S.average

Agricultural & Other Activities (Residential, Commercial,

Industrial, Transportation, Wastewater treatment)

GHG emissions

EPAGHGRP (EPA, 2016)

Facility

EPANEI (EPA, 2014)

County

An pollutants

EPANEI (EPA, 2014)

County

Water pollutants

(Agricultural) SWAT (Khanal et al., 2018)

HUC8

(Other activities) EPA (Ohio EPA, 2016)

HUC4

Water withdrawal

EnvuoAtlas (EPA, 2018b)

HUC8

Water consumption

USGS (Solley et al., 1998)

Ohio

Natural gas use

EIA (EIA, 2018b)

Ohio

Electricity use

EIA (EIA, 2018d)

Ohio

Ecosystem Supplies

Carbon sequestration

i-Tree Landscape {i-Tvee Landscape, 2018)

HUCS

An quality regulation

i-Tree Landscape {i-Tvee Landscape, 2018)

HUCS

Water quality regulation

(Kadlec, 2008, 2016)

Average

Water provision

AWARE (Boulay et al., 2018)

HUC2

Natural gas provision

(Le Quere et al., 2017)

Global

Thermoelectric power generation

In the MRW, there are two coal-fired steam turbine power plants and three natural gas-fired combined cycle (NGCC) power plants, as shown in Figure 1. The Muskingum River Power Plant was retired in 2015 due to environmental regulations (Gearino, 2013). However, since our study is for 2014, we assume that the Muskingum River Power Plant is still operating in order to keep the temporal consistency of data.

In terms of the power generation technology of thermoelectric power plants, 99% of coal-fired power plants in the U.S. employ steam turbine boilers, while 84% of NG-fired power plants in the U.S. employ combined cycle boilers (Wang, 2016). Since five power plants in the MRW are also operated by using these generation technologies, we only consider these two types of power generation technologies in this study.

Fossil power generation is responsible for about 45% of freshwater withdrawals in the U.S. (Maupin et al., 2014). Most water withdrawn is used for the cooling of boilers. Depending on which cooling methods are employed in the power plant, water and energy requirements are varied. Once-through cooling technology, also known as the open-loop cooling system, withdraws a massive amount of water but returns most of it at a wanner temperature to the watershed. The once-through cooling system has mainly been installed in power plants in the eastern U.S. On the other hand, recirculating cooling technology, also known as the closed-loop cooling system and cooling tower, withdraws only a fraction of the water that systems require, recirculates water, but consumes most of it through evaporation from the cooling tower. Therefore, recirculating cooling technology has higher water consumption than once- through cooling technology, even though its amount of water withdrawn is significantly lower. Also, it has lower electricity generation efficiency and is more expensive than once-through cooling technology (Tawney et al., 2005). The recirculating cooling system is widespread in the western U.S. In contrast to those wet cooling methods, the diy cooling technology uses no water, but requires more energy and higher capital and operation costs, and results in lower generation efficiency than wet cooling technologies. The lower generation efficiency means that more fossil resources are required to generate electricity, and thus, it will increase the impacts from upstream processes, such as mining and transportation of fossil fuels.

Among the five power plants in the MRW, only one coal-fired plant, the Muskingum River Power Plant, employs once-through cooling technology, the other four plants employ the recirculating cooling technology. In this study, three cooling technologies (once-through, recirculating, and dry cooling) are considered as technological alternatives for thermoelectric activity. It is reported that 0.3-1% and 2-4% reductions in generation efficiency are expected for thermoelectric power plants in Texas if the once-through cooling system is converted to recirculating and diy cooling systems, respectively (Loew et al., 2016). Also, 0.60-0.63 cents/kWli of cost is required for the plant operator to retrofit a recirculating cooling system to a diy cooling system.

 
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