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Policy Analysis
Air Emissions Damages from Municipal Drinking Water Treatment Under Current and Proposed Regulatory Standards Daniel B Gingerich, and Meagan S Mauter Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03461 • Publication Date (Web): 23 Aug 2017 Downloaded from http://pubs.acs.org on August 25, 2017
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Air Emissions Damages from Municipal Drinking Water Treatment Under Current and
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Proposed Regulatory Standards
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Daniel B. Gingerich1 and Meagan S. Mauter1,2,* 1
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213 2 Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 *Contact Author:
[email protected] Abstract Water treatment processes present inter-sectoral and cross-media risk trade-offs that are
13
not presently considered in Safe Drinking Water Act regulatory analyses. This paper develops a
14
method for assessing the air emission implications of common municipal water treatment
15
processes used to comply with recently promulgated and proposed regulatory standards,
16
including arsenic, lead and copper, disinfection byproducts, chromium (VI), strontium, and
17
PFOA/PFOS. Life-cycle models of electricity and chemical consumption for individual drinking
18
water unit processes are used to estimate embedded NOx, SO2, PM2.5, and CO2 emissions on a
19
cubic meter basis. We estimate air emission damages from currently installed treatment
20
processes at US drinking water facilities to be on the order of $500 million USD annually. Fully
21
complying with six promulgated and proposed rules would increase baseline air emission
22
damages by approximately 50%, with three-quarters of these damages originating from chemical
23
manufacturing. Despite the magnitude of these air emission damages, the net benefit of currently
24
implemented rules remains positive. For some proposed rules, however, the promise of net
25
benefits remains contingent on technology choice.
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1.0 Introduction The Safe Drinking Water Act (SDWA) provides regulatory authority to the US federal
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government to create enforceable standards for drinking water quality and safety.1 These
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standards have enabled extraordinary gains in public health,2 and retrospective analyses of
32
historic drinking water quality regulations indicate that the benefits have far exceeded any
33
compliance costs.2, 3 Fully assessing these benefits and costs for emerging drinking water
34
contaminants is more challenging, particularly when contaminant removal processes impose
35
systemic risk tradeoffs.4
36
The most notable example of these risk trade-offs in drinking water regulatory analyses is
37
for disinfection and disinfection byproducts. In establishing the Long-Term Enhanced Surface
38
Water Treatment Rules,5 the EPA set regulatory standards to balance the competing risks of
39
acute illness from microbial contamination with the risks of cancer from disinfection
40
byproducts.6 There is also a growing body of research on inter-sectoral risk trade-offs involving
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drinking water, including the use of methyl tert-butyl ether (MTBE) as a gasoline additive,7
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bromide for mercury control at power plants,8, 9 and atrazine as a pesticide.10 But the
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incorporation of inter-sectoral and inter-media (e.g. water and air or water and soil) trade-offs
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into regulatory analyses is often limited by the “bounded oversight” of the regulators responsible
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for designing drinking water regulations.7, 11 Researchers have argued that benefit-cost analysis
46
can address bounded oversight to express the benefits and damages to a variety of media.12, 13
47
Even with benefit-cost analysis, however, an analyst must make a deliberate choice to include
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cross-media impacts in the scope.
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Drinking water regulatory analyses have also neglected to consider trade-offs that occur over the life-cycle of the water treatment system, most notably the operation phase. Drinking
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water systems comply with SDWA rules by installing separation processes that rely on
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electricity and chemicals.14, 15 Life-cycle assessments (LCAs) of drinking water systems have
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demonstrated that the majority of impacts associated with drinking water treatment occur as a
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result of electricity and chemical consumption during plant operation.15-18 These impacts include
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emissions of greenhouse gasses (GHGs) and the criteria air pollutants (CAPs) NOx, SO2, and
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particulate matter from electricity generation and chemical manufacturing. These indirect
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emissions of GHGs and CAPs produced over the life cycle of water treatment impose human
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health, environmental, and climate (HEC) damages.19-23
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While there are a multitude of drinking water treatment LCAs that quantify the energy
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intensity or GHG and CAP emissions from water treatment,15-17, 24-29 we are unaware of any that
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quantify the human health damages associated with these emissions. Furthermore, the vast
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majority of these LCAs were performed for a single treatment train, rather than for the diverse
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set of processes currently installed at drinking water treatment facilities around the US. Accurate
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estimates of the air emission damages from US water treatment plants under current and future
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regulatory scenarios is further confounded by the high regional variability in the emissions
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factors associated with chemical and electricity process inputs. In the absence of quantitative
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methods for estimating air emission damages from existing and emerging water treatment
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processes, rulemaking activities have been unable to consider competing risks from diminished
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air or water quality.
70
This work fills this gap by developing and applying a quantitative method for evaluating
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the life-cycle air emission damages from drinking water treatment. We build life-cycle models
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of electricity and chemical consumption for drinking water unit processes, estimate the
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embedded smokestack emissions of NOx, SO2, PM2.5, and CO2, and provide spatially resolved
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estimates of associated damages to human health and the environment. We apply this
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methodology to estimate the air emission damages from installed water treatment processes at all
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US drinking water facilities. Finally, we evaluate the air-water risk tradeoffs for six proposed
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and promulgated drinking water regulations.
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2.0 Methods
79
2.1 Estimating Air Emission Damages from Drinking Water Treatment
80
To calculate the air emission damages associated with drinking water treatment processes
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we combine treatment level-facility data with state-level data on electricity consumption,
82
chemical manufacturing, and air emission damages (Figure 1).
83 84
Figure 1. Method for calculating the drinking water air emission damages and net benefits or
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net costs for the regulations included in this analysis.
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For this analysis, we focus on six different contaminant/regulations and compliance
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technologies: Arsenic,30 Lead and Copper,31 Disinfectant By-Products (DBPs),5 Hexavalent
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Chromium,32 Strontium,33 and Perfluorooctanoic Acid (PFOA) and Perfluorooctyl Sulfonate
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(PFOS)34 (Table 1, Supporting Information Section 1.0). Three of these rules (Arsenic, Lead and
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Copper, and DBP) are finalized. The other three rules, Hexavalent Chromium, Strontium, and
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PFOA/PFOS, are at various stages in the regulatory process. These rules will require the
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installation of new treatment processes at non-compliant facilities. Analysis on the air emission
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impacts of regulations considers only the effects of installing new processes at non-compliant
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plants to meet proposed standards. If a facility already has a compliance technology installed
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and is compliant with the standard, we do not consider it in evaluating the air emissions
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associated with complying with that rule.
97 98
Table 1. Rules and Compliance Technologies Rule
Compliance Technologies
Arsenic Iron Co-Precipitation Lead and Copper Corrosion Inhibitor DBP
GAC Adsorption
Chromium (VI) Strontium PFOS/PFOA
Reverse Osmosis Lime Soda Ash Softening Reverse Osmosis / GAC Adsorption
Standard 10 ug/L Lead 15 ug/L Copper 1.3 mg/L TTHM 80 ug/L HAA5 60 ug/L 10 ug/L 1.5 mg/L Total 70 ng/L
Number of Non-Compliant Systems 1,086 2,757 1,697 25 113 27,000
99 100
Drinking Water System Data
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We use data from the Safe Drinking Water Information System (SDWIS),35 Unregulated
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Contaminant Monitoring Rule (UCMR),36 and Information Collecting Rule (ICR) 37 (SI Section
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2.0) to identify the (1) state, (2) installed treatment technologies (SI Section 3.0), and (3) volume
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of water. In total, 47,500 drinking water systems serving 288 million people were analyzed.
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We use the location of each facility reported in SDWIS to identify the appropriate statelevel marginal emissions factor38 for generating electricity used during water treatment. SDWIS
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also identifies currently installed treatment processes that we use in developing a model of
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baseline emissions from drinking water treatment. SDWIS does not report water production, and
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so we estimate total annual water production for system i, Vi [m3/yr], as the product of SDWIS
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reported population served, Popserved [person], and the state-level average per capita water
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consumption per year, Apc [m3/person·yr],39 as shown in Equation 1. 𝑉𝑖 = 𝐴𝑃𝐶 𝑃𝑜𝑝𝑖,𝑠𝑒𝑟𝑣𝑒𝑑 (1)
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We determine facilities that will need to install additional treatment technologies to
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comply with the six water quality rules (Table 1) by comparing the MCL for each rule to water
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quality data reported in the UCMR and the ICR. If water quality data is not available for a
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facility, we apply state-averaged water quality data for that facility. We assume that any
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compliance technologies that are installed are operated to in order to achieve compliance with
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the regulation.
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Life-Cycle Inventory of Air Emissions from Drinking Water Systems
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For each facility in our dataset, we use SDWIS35 to inventory the water treatment
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technologies currently installed in the “baseline” treatment train. For non-compliant systems, we
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also inventory technologies necessary to bring a “regulated” treatment train into compliance with
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each of the six pending or proposed water quality rules (SI Section 1.0). Average electricity27, 40
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and chemical inputs15, 27, 41 for each of these treatment processes is obtained from the published
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literature and reported in SI Sections 2.0 and 3.0 and Tables S1-S3. Finally, we estimate the air
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emissions embedded in these electricity and chemical inputs in the year 2014.
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𝐸𝑙𝑒𝑐 The mass of annual air emissions associated with electricity consumption, 𝑀ℎ,𝑖,𝑗 [g/yr] is
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calculated for each pollutant j from drinking water facility i under scenario h of either the
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baseline scenario or new regulation scenario using Equation 2. Emissions are the product of the
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volume of water produced at facility i, Vi [m3/yr], the total electricity consumption of the unit
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processes, g, that are installed in the baseline or newly-regulated scenario, h, Eg,hW [kWh/m3], and
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the marginal emissions factors per kWh for air pollutant j in state l, emf,j,l [g/kWh].38, 42 The
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emissions factors for CO2, NOx, and SO2 are marginal emission factors, as only a small
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percentage of US electricity generation is consumed by water treatment processes.43, 44 Marginal
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emission factors are not available for PM2.5 and so we use state-level average emission factors
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from the EPA Emission Inventories.42 Electricity is assumed to be generated in the state where
137
the drinking water facility is located. 𝐸𝑙𝑒𝑐 𝑊 𝑀ℎ,𝑖,𝑗 = 𝑉𝑖 𝐸𝑔,ℎ 𝑒𝑚𝑓,𝑗,𝑙 (2)
138 139 140
𝑉𝑙 ) 𝑙 𝑉𝑙
𝐶 𝐶 𝐷 𝐷 𝑀ℎ,𝑖,𝑗 = ∑𝑓 𝑉𝑖 𝑄𝑖,𝑓,𝑗 (𝑒𝑐𝑚,𝑓,ℎ + ∑𝑑 𝐸𝑑,𝑓 𝑒𝑑,ℎ + 𝐸𝑓𝑊 ∑𝑙 𝑒𝑚𝑓,𝑙,ℎ ∑
(3)
Similarly, the mass of annual air emissions associated with chemical consumption by
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𝑐 each water treatment facility, 𝑀ℎ,𝑖,𝑗 in [g/yr], is calculated using Equation 3. Air emissions from
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chemical manufacturing originate from three sources. The first source is emissions released
143
𝐶 directly during the manufacturing of chemical f, 𝑒𝑐𝑚,𝑓,ℎ in [g-emissions/g-chemicals]. The
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second source of emissions is from the combustion of thermal energy to drive chemical
145
𝐷 manufacturing, which is the product of the energy consumed from fuel source d, 𝐸𝑑,𝑓 in [MJ/g-
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𝐷 chemical], and emission per unit of thermal energy, 𝑒𝑑,ℎ in [g-pollutant/MJ]. The final source is
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emissions from electricity consumed in chemical manufacturing which is the weighted average
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of the grid emissions, ∑𝑙 𝑒𝑚𝑓,𝑙,ℎ ∑
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to produce a unit of chemicals, 𝐸𝑓𝐶 in [kWh/g-chemical]. This weighting is done according to a
150
state’s chemical manufacturing sector size and we assume chemical manufacturing follows the
151
nationwide distribution in chemical production.45 The sum of these emissions per unit of
𝑉𝑙 𝑙 𝑉𝑙
in [g-emissions/kWh] multiplied by the electricity consumed
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chemical is then multiplied by the water required to be treated at facility i, Vi in [m3/yr], and the
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chemical dosage, Qi,f [g-chemical/m3]. Additional detail about the methods used to calculate
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chemical emissions can be found in our previous work.46 We also perform sensitivity analyses
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(SI Section 4.0) on assumptions about the geographic distribution of chemical manufacturing and
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binding air pollution regulations.
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Damages from Drinking Water Systems
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To calculate the associated air emission damages from drinking water systems at the
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facility-level, we use AP2,21 EASIUR,47 and the social cost of carbon23 to estimate the damages
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per ton of additional pollutant j occurring in state l, dj,l in [$/g]. In the main manuscript we report
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health and environmental damages from CAPs using AP2. Note that AP2 includes both human
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health and environmental damages of CAPs, but the human health damages are several orders of
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magnitude larger than the environmental damages due to reduced agricultural crop and timber
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sales. The SI reports results using the EASIUR model, which exclusively models human health
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damages. Both AP2 and EASIUR account for atmospheric transformation of pollutants,
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including damages associated with the formation of secondary aerosols. The disagreement
167
between AP2 and EASIUR health damage estimates stem from differences in underlying
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atmospheric transport models and atmospheric transformations. Damages from these models are
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calculated in 2014 USD with a value of a statistical life of $8.7 million.48
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Air emission damages associated with electricity consumption are calculated at the
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𝐸𝑙𝑒𝑐 facility-level, 𝐷𝑖,ℎ in [$/yr], by multiplying the amount of electricity consumed at facility i by
172
𝑑𝑗,𝑙 (Equation 4). Air emission damages associated with the production of chemicals consumed
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in water treatment are calculated for each state l as the product of 𝑑𝑗,𝑙 and estimated mass of air
174
emissions from chemical manufacturing in that state (Equation 5).
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𝐸𝑙𝑒𝑐 𝐸𝑙𝑒𝑐 𝐷ℎ,𝑖 = ∑𝑗 𝑑𝑗,𝑙 𝑀ℎ,𝑖,𝑗
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𝐶 𝐷ℎ,𝑙 = ∑𝑗 𝑑𝑗,𝑙 𝑀𝐶ℎ,𝑖,𝑗 ∑𝑙=𝐿 𝑉
𝑉
(4) (5)
𝑙 𝑙
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The total damages nationwide for treatment train h, Dh in [$/yr], is given by Equation 6.
178
𝐸𝑙𝑒𝑐 𝐶 𝐷ℎ = ∑𝑖 𝐷𝑖,ℎ + ∑𝑙 𝐷ℎ,𝑙
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2.2 Benefit-Cost Analysis of Drinking Water Regulations
(6)
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We compare the damages calculated using Equation 6 to the benefits reported in the
181
regulatory documentation for Arsenic,30 the Lead and Copper Rules,31 and the Disinfection
182
Byproduct Rules.5 Costs (C) considered in these regulatory analyses include technology
183
installation and regulatory oversight. The costs do not include damages from embedded air
184
emissions, as the EPA did not calculate them during the BCA process. Benefits (B) include
185
health benefits and other environmental benefits. The net benefits (N) of a rule are calculated
186
using Equation 7.
187
𝑁 = 𝐵 − 𝐶 − 𝐷ℎ
188
For the three rules that are still in development, we use published estimates of
(7)
189
compliance technology costs to calculate the health benefits from improved water quality
190
necessary for the rule to provide a net benefit to society.49
191
2.3 Evaluating Regulatory Compliance Options
192
The EPA recommends two compliance technology options for PFOA/PFOS: reverse
193
osmosis or granular activated carbon. In the main analysis laid out in Section 2.1, we model
194
plants installing granular activated carbon adsorption processes to comply with the PFOA/PFOS
195
health advisory. We repeat the calculations in Section 2.1 using reverse osmosis as the
196
compliance technology to explore the difference in damages resulting from selecting an
197
alternative technology.
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2.4 Forecasting Emissions from Electricity Consumption The marginal emission factors from electricity generation are expected to decrease as
200
coal fired power plants are replaced by natural gas plants and renewable energy sources. This
201
transition may, in turn, reduce the embedded air emission damages from drinking water
202
treatment. We use EIA Annual Energy Outlook 2017 Reference case with the Clean Power
203
Plan50 forecasts of electricity generation, Gk,m [kWh], to calculate national average shares of
204
electricity from fuel m (coal, natural gas, diesel, and zero operating emission energy sources) in
205
year k between 2015-2050. This reference case assumes that the US upholds its CO2 reduction
206
commitments as outlined in the Paris Agreement. We also include two additional cases, the EIA
207
AEO Reference case without the Clean Power Plan and the EIA AEO high oil and gas resource
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and technology scenario, as alternative future energy portfolios. We then calculate national
209
average emission factor forecasts, eaf,m [g/kWh], over this interval for SO2, NOx, PM2.5, and CO2
210
using average emission factors from fuel source coal, natural gas, and diesel.51 We then multiply
211
national average emission factor forecasts by the amount of electricity consumed to drive
212
baseline and regulatory treatment trains and average damages per mass of air pollution values in
213
order to calculate expected damages through 2050 (Equation 8).
214
𝑊 𝐷𝑘,ℎ = ∑𝑗(𝑑𝑗 ∑𝑖 𝑉𝑖 ∑𝑔( 𝐸𝑔,ℎ ∗
𝐺𝑘,𝑚 𝑒𝑎𝑓,𝑚 ∑𝑙 𝐺𝑘,𝑚
))
(8)
215
Because we use marginal emission factors for the main analysis and average emission factors for
216
forecasting, Equation 8 overestimates the damages. We correct for this overestimation, 𝐷̃ 𝑘,ℎ
217
[$/yr], by multiplying the ratio of calculated results for 2014 from Equation 5, Dh [$/yr],
218
forecasted results for 2014 from Equation 8, Dk,h [$/yr] (Equation 9).
219
𝐷̃ 𝑘,ℎ =
𝐷ℎ 𝐷ℎ,𝑘=2014
𝐷𝑘,ℎ (9)
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3.0 Results and Discussion
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3.1 Air Emission Damages from Operating Baseline and Compliant Treatment Trains
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We estimate that baseline operation of water treatment plants consumed 2800 GWh of
224
electricity, consumed 1.5 million tons of chemicals, and generated $493 million dollars in air
225
emission damages in 2014 (expressed in 2014 dollars and using a value of a statistical life of
226
$8.69 million) (Figure 2A, 2C, and 2E). Emissions from chemical manufacturing contributes
227
73% of the damages in the baseline treatment train. For comparison, air emission damages
228
calculated using EASIUR amount to $533 million ($135 million from electricity generation and
229
$398 million from chemical manufacturing) as shown in SI Section 5.2, Figure S1, and Table
230
S10 .The damages associated with operating baseline water treatment are several orders of
231
magnitude lower than the benefits of avoided illness and death from untreated drinking water.2
232
These air emission damages are also several orders of magnitude smaller than the approximately
233
100,000 deaths from air emissions that occur annually in the US.52
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Figure 2. Per capita air emission damages associated with operating drinking water treatment
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processes under current and future regulatory scenarios. State-level damages embedded in
239
electricity consumption by water treatment processes for the (A) baseline treatment train and the
240
(B) regulated treatment train assuming compliance with all promulgated and proposed SDWA
241
regulations. State-level damages embedded in chemical consumption by water treatment
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processes for the (C) baseline treatment train and the (D) regulated treatment train. Total air
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emissions damages for the (E) baseline treatment train and the (F) regulated treatment train.
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Emissions and damages are tabulated in SI Tables S8 and S9 and SI Section 5.1. Results
245
calculated using EASIUR to price CAP damages can be found in SI Section 5.2, Figure S1, and
246
Tables S10 and S11.
247 248
Achieving compliance with the six drinking water regulations increases air emission
249
damages by $242 million (in 2014$) annually using the compliance technologies listed in Table
250
1 and GAC for PFOA/PFOS removal (Figure 2, B, and D). This represents an increase of 49%
251
from the emissions associated with the baseline treatment train. Of this $242 million in
252
damages, 76% are damages from chemical manufacturing. Over 84% of these damages, $205
253
million (in 2014$), stem from compliance with the PFOA/PFOS Health Advisory at 27,000
254
drinking water facilities nationwide. EASIUR modeled air emission damages from regulatory
255
compliance estimate that total damages equal $796 million, or an additional $263 million beyond
256
baseline damage estimates using EASIUR ($41 million from electricity generation and $222
257
million from chemical manufacturing) as shown in SI Section 5.2, Figure S1, and Table S11.
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Emissions and damages increases estimated for compliance with each of the six regulations are
259
broken down in SI Section 6.0, Tables S12-S17, and Figures S2-S7.
260 261 262 263 264 265
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3.2 Benefit-Cost Analysis of Drinking Water Regulations
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Table 2. Benefit-Cost analysis for the six drinking water regulations after accounting for
268
estimated air emission damages. Benefits
Contaminant Finalized Rules Arsenic30 DBP
5
Lead & Copper31
Costs/Damages Compliance Electricity Costs Damages 3 ($/m in 2014$)
Net Chemical Damages
0.14
0.16
0.0005
0.000002
-0.023
3.13
1.08
0.0013
0.0080
2.04
8.36
1.35
0.0006
0.0003
7.01
Rules Under Consideration Chromium (VI)
≥0.25*
0.2049
0.024
0.0014
≥0
Strontium
≥0.43*
0.4053
0.0008
0.042
≥0
PFOA/PFOS**
≥0.61*
0.6049
0.0015
0.0078
≥0
*Rules that are under consideration do not have published estimates for their benefits and compliance costs. **Using Granular Activated Carbon as the compliance technology.
269 270
For the three finalized rules (Arsenic, DBPs, and Lead and Copper), the signs on the
271
benefit-cost analysis do not change with the inclusion of air emission damages (Table 2). The
272
DBP and Lead and Copper rules had large benefits to society, and accounting for air emissions
273
damages does not change this conclusion. The arsenic rule was a net cost to society without
274
incorporating air emissions from drinking water; including air emissions in the benefit-cost
275
analysis only increases the cost.
276
For the three rules that are not yet finalized, Table 2 presents the minimum benefits
277
required given estimates of air emission damages from this analysis and literature-based
278
compliance technology costs.49, 53 On a per cubic meter basis, air emission damages contribute 2-
279
11% of the total costs to society for these rules. Air emissions are therefore a small, but non-
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negligible contributor to these overall costs. The benefits required for these rules to impart net
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social benefits range from $0.25/m3 to $0.61/m3 (in 2014$).
282
There are several unquantifiable co-benefits of adopting the six drinking water
283
regulations that are not accounted for in this analysis. These include the reduction of unregulated
284
contaminant concentrations associated with the advanced treatment technologies that are
285
installed to comply with these rules. There is also the possibility that, in the process of
286
complying with new water quality regulations, monitoring and enforcement of existing water
287
quality regulations is improved.
288
3.3 Evaluating Regulatory Compliance Options
289 290
Figure 3. Air emission damages from reverse osmosis and granular activated carbon treatment
291
for PFOA/PFOS removal at non-compliant drinking water facilities across the United States
292
using state-level marginal emissions factors for NOx, SO2, and CO2 and state-level average
293
emissions factors for PM2.5. The error bars show the uncertainty in the location and presence of
294
binding regulations affecting emissions from the chemical manufacturing sector (SI Section 4.0)
295
and Tables S4-S7.
296 297
Quantifying the air emission damages of drinking water treatment processes can also assist in compliance technology selection. Of the two compliance options for PFOA/PFOS
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removal, reverse osmosis is the highest damage alternative (Figure 3). Using reverse osmosis to
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comply with the PFOA/PFOS standards imposes air emission damages of $1.2 billion annually
300
(in 2014$). The use of GAC to achieve compliance with PFOA/PFOS imposes air emission
301
damages of $205 million/yr (in 2014$), a sixth of the damages from reverse osmosis. The
302
primary source of air emission damages from RO is the electricity used to drive the process,
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rather than from emissions embedded in chemical consumption. In contrast, granular activated
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carbon leads to more damages from chemical manufacturing than reverse osmosis, with
305
subsequently more uncertainty.
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Reverse osmosis and granular activated carbon have different removal efficiencies for
307
PFOA/PFOS, with RO producing higher quality water. This sets up trade-off between reducing
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health risks from PFOA/PFOS in drinking water and minimizing the environmental and health
309
risks from criteria air pollutants and greenhouse gasses. To account for this additional $1.0
310
billion in air emission damages annually, reverse osmosis would need to save an additional 120
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statistical lives through PFOA/PFOS concentration reduction. These additional statistical lives
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could also be saved by the co-benefits of RO by producing higher quality water.
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3.4 Future Air Emission Damages from Electricity Consumed in Drinking Water Treatment
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Figure 4. Projected air emission damages from electricity generated to treat US drinking water
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with the baseline treatment train and the additional emissions that result from compliance with
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current and proposed drinking water standards. The grid mix follows the AEO 2017 Reference
318
case with the Clean Power Plan. Forecasts for the AEO 2017 Reference case without the Clean
319
Power Plan and the High oil and gas resource and technology scenario differ by less than 7%
320
(details reported in SI Section 7.0). N.B. That this figure does not include damages resulting
321
from the electricity consumed during chemical manufacturing.
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As the grid evolves to rely less on fossil fuel sources, damages from air emissions are
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expected to decrease (Figure 4). By 2050, annual damages associated with emissions from
324
electricity generation that result from compliance with these six standards decreases by $19
325
million per year from the 2015 level of $40 million. This reduction in damages from electricity
326
will lower the required benefits presented in Table 2 to achieve net benefits from these drinking
327
water rules. Projected air emission damages for two alternative electricity grid scenarios,
328
including scenarios without the Clean Power Plan and with high natural gas use differ by less
329
than 7% (SI Section 7.0 and Figure S8). The robustness of these results to changes in the
330
electricity mix reflect the relatively small fraction of damages that originate from electricity
331
consumption.
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4.0 Implications
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Stronger epidemiological evidence of health impacts from contaminated water, enhanced
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public awareness of water quality issues, and improved analytical techniques for detecting
335
aqueous contaminants are each drivers for stricter water quality regulations.1, 54 While the
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counter-argument to installing the advanced treatment technologies necessary for compliance has
337
historically been cost, we propose that the very real risks of air emission damages associated
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with increased electricity or chemical consumption of water treatment processes should also be
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considered. These incremental air emission damages may outweigh the incremental benefits of
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cleaner water enabled by stricter drinking water regulatory limits, but establishing this balance of
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cost and benefits is difficult to establish a priori.
342
Given that air emission damages are difficult to establish a priori and useful in informing
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regulatory concentration limits, we conclude that there are merits to regulatory assessment
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processes explicitly considers the life-cycle tradeoffs between improved water quality and
345
reduced air emissions. This process may inform the selection of concentration limits that
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maximize human health benefits, technologies for regulatory compliance, or investment
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priorities in the water, chemical, and electricity generation space. While performing this analysis
348
will increase EPA workload, screening approaches such as Economic Input/Output LCA may
349
allow the EPA to assess the need for the more robust analysis described in this manuscript.55
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Adapting the regulatory assessment process to include life-cycle air emissions may also
351
broaden the scope of environmental justice analyses. This analysis demonstrates that spatial
352
distribution of the damages, and not simply the water quality benefits, varies across the United
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States and should be considered in evaluating regulations. Areas with high-levels of coal-fired
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electricity generation or chemical manufacturing may experience damages from air emissions in
355
excess of benefits from improved drinking water quality. Performing spatially-resolved air
356
emissions analyses allows the EPA to quantify these trade-offs as part of their standard
357
environmental justice analyses.
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Finally, this analysis supports the ongoing transition from single-media focused
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regulations (e.g. drinking water) towards more holistic analyses that account for the
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countervailing risks analyzed in this paper. Previous examples of the EPA moving to holistic
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regulatory activity includes the cluster rules for the pulp and paper industry56 and Executive
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Order (EO) 13211 mandating that all regulations, including drinking water regulations, undergo
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an energy inventory if they are deemed “economically significant.”43 Unfortunately, it is not
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standard practice for analyses performed under EO 13211 to assess emissions associated with
365
this electricity generation or incorporate the damages into benefit-cost analyses performed under
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EO 12866. Even if damages from the emissions associated with electricity generation were
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included in EPA BCAs for drinking water treatment, the emissions from chemical manufacturing
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would be overlooked. As chemical manufacturing damages contribute roughly three times as
369
much as electricity generation, their inclusion is important in ensuring a comprehensive analysis
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of these trade-offs.
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In short, more rapid adoption of environmental regulatory frameworks that account for
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inter-sectoral and cross-media risk trade-offs should be a priority at both the national and state
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levels.
374
Acknowledgements
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This work was supported by the National Science Foundation under award number CBET-
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1554117.
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Supporting Information
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The supporting information contains descriptions of 1) the six drinking water standards with
379
compliance modeled in this analysis; 2) data sources; 3) drinking water treatment unit process
380
description and inputs; 4) chemical manufacturing location sensitivity analyses; 5) emissions and
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damages from drinking water treatment using AP2 and EASIUR; 6) emissions and damages
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from the individual drinking water standards; and 7) air emission damages using alternative grid
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forecasts.
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Nomenclature
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A:
Per capita annual water consumption [m3/person·yr]
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B:
Benefits from a drinking water regulation [$/yr]
387
C:
Compliance costs from a drinking water regulation [$/yr]
388
D:
Air emission damages for drinking water treatment [$/yr]
389
̃: 𝐷
Corrected damages forecast [$/yr]
390
d:
Damages per unit of NOx, SO2, PM2.5, and CO2 [$/g]
391
E:
Energy consumption [kWh/m3], [kWh/g-chemical], or [MJ/g-chemical]
392
e:
Emissions factor per unit of energy [g/kWh] or [g/MJ]
393
G:
Annual electricity generation [kWh]
394
M:
Annual mass of NOx, SO2, PM2.5, or CO2 emissions [g/yr]
395
N:
Net benefits or costs from a drinking water regulation [$/yr]
396
Pop:
Population served by a facility [people]
397
Q:
Chemical dosage [g-chemical/m3]
398
V:
Annual value of products from the chemical manufacturing sector [$]
399
V:
Annual water production [m3/yr]
400
W:
Electricity consumption for water treatment process [kWh/m3]
401
Subscripts
402
af:
Average emissions factor
403
cm:
Chemical manufacturing
404
d:
Thermal fuel
405
f:
Chemical
406
g:
Unit process
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h:
Treatment train (baseline or newly-regulated)
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i:
Drinking water facility
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j:
Air pollutant (NOx, SO2, PM2.5, or CO2)
410
k:
Year
411
l:
State
412
m:
Fuel source for electricity generation
413
\mf:
Marginal emissions factor
414
PC:
per capita
415
served:
Population served by a facility
416
Superscripts
417
C
:
From chemical manufacturing
418
D:
From thermal fuel combustion
419
Elec
420
W
421
References
422 423 424 425 426 427 428 429 430 431 432 433 434 435
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