How Can Clean Drinking Water Be More Available In Rural Areas In America With Renewable Energy

Abstract

Many households in the The states face issues of incomplete plumbing and poor water quality. Prior scholarship on this issue has focused on one dimension of h2o hardship at a fourth dimension, leaving the total picture incomplete. Here nosotros complete this picture by documenting the full scope of water hardship in the United States and find evidence of a regionally-clustered, socially unequal nationwide household water crisis. Using data from the American Customs Survey and the Ecology Protection Agency, we bear witness there are 489,836 households lacking complete plumbing, 1,165 community water systems in Safe Drinking H2o Act Serious Violation, and 21,035 Clean Water Human action permittees in Significant Noncompliance. Further, nosotros demonstrate this crisis is regionally amassed, with the specific spatial pattern varying past the specific course of water hardship. Elevated levels of water hardship are associated with the social dimensions of rurality, poverty, indigeneity, instruction, and age—representing a nationwide environmental injustice.

Introduction

Both in and out of the country, most assume that residents of the The states live with close to universal access to drinkable water and sanitation. The United nations Sustainable Development Goals Tracker, which tracks progress toward meeting Sustainable Development Goal Number 6—calling for universal access to drink water and sanitation for all by 2030—estimates that 99.ii% of the Usa population has continuous access to drink water and 88.9% has access to sanitation¹. Past percentages and the lived experience of almost Americans, this appears accurate. The American Customs Survey shows that from 2014 to 2018 only an estimated 0.41% of occupied US households lacked access to complete plumbing—significant access to hot and common cold h2o, a sink with a faucet, and a bath or shower. Although this relative per centum may be low, this 0.41% corresponds to 489,836 households spread unevenly across the country, making the absolute number quite troubling. These numbers become even more dramatic when we broaden our telescopic to poor household water quality, where the estimates nosotros provide in this paper show the result affects a far greater share of the population (Tabular array ane).

Tabular array 1 Estimates of water hardship in the The states.

Full size table

This study builds on a growing torso of evidence showing admission to plumbing, water quality, and basic sanitation are defective for a disturbingly large number of US residents by providing a definitive picture of the ongoing household h2o crisis in the United States. Water and sanitation problems take been a growing business organization in the United States, specially amongst policy organizations, for the by twenty years^{2,3,iv,5,half dozen,7,8,ix,10}. For example, the now-dated Still Living without the Basics report used Census data from 2000 to show that more than 670,000 households (0.64% of households and 1.seven meg people) lacked access to consummate plumbing facilities⁷. Further, the Water Infrastructure Network, published a report in 2004 citing a gap of $23 billion betwixt available funding and needed h2o and sanitation infrastructure investments^vi. In line with this, the American Society of Civil Engineers has repeatedly given the United States a "D" grade for h2o infrastructure, and "D-" for wastewater infrastructure in their annual "Infrastructure Study Card"¹¹. Although water hardship in the United States has experienced some academic attending, much of the work has get dated and has generally focused on a single dimension of the issue at a fourth dimension—for example, contempo scholarship has focused on exclusively incomplete plumbing^iii,4,9, water quality^5,x, or on merely urban parts of the country². This has left our understanding of the scope of the consequence incomplete. In this paper, we estimate and map the full scope of water hardship, including both incomplete plumbing and poor h2o quality across the entire United States, to complete this picture.

Prior work from academics and policy groups on dimensions of water hardship has found water access issues pattern forth common social inequalities in the United States. The Natural Resources Defense Council released a report demonstrating the disproportionate impact on people of colour posed past Safety Drinking Water and Make clean Water regulatory burdens¹², which congenital on similar peer reviewed findings^xiii,14. Furthermore, both policy papers and peer reviewed studies have analyzed Census information to gauge the population lacking access to consummate plumbing facilities and make clean h2o^{ii,3,iv,5,half dozen,seven,8,ix,10,12}. The studies advise low-income and not-White people—particularly indigenous populations who continue to face injustices related to legacies of settler colonialism^xv—are significantly more probable to have incomplete plumbing and unclean water^3,12. Further, it appears incomplete plumbing may be a disproportionately rural issue, while poor water quality may be a disproportionately urban upshot^five,9. Direct comparisons, as we perform here, are needed to fully establish the variability of this inequality between dimensions of water hardship.

The prior scholarship on the inequitable distribution of plumbing and pollution speaks to the well-documented environmental injustices found throughout the United states of america. Environmental injustice, significant the absenteeism of "fair handling and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of ecology laws, regulations, and policies" (p. 558)¹⁶, has been documented in the United States along the social dimensions of income^17,18, poverty^nineteen, race and ethnicity^20,21, age²², education^22,23, and rurality^22,24,25. Based on the show of prior work on water hardship, it is clear household water access represents an ongoing environmental injustice in the U.s.^five. All the same, the specific dimensions of this injustice, and how they vary between type of water hardship remain largely unknown. To address this gap, we estimate models of water injustice for the previously identified social dimensions at the county level for elevated levels of both incomplete plumbing and poor water quality.

Results

Level of h2o hardship in the U.s.

Based upon the most recent bachelor information reported by both the Us Census Agency via the American Community Survey and the Environmental Protection Agency via Enforcement and Compliance History Online, we find that incomplete plumbing and poor water quality affects millions of Americans as of 2014–2018 and August 2020, respectively (Tabular array ane)^26,27. A full of 0.41% of households, or 489,836 households, lacked complete plumbing from 2014–2018 in the Us. Further, 509 counties, representing over 13 million Americans, have an elevated level of the issue where >1% of household do non have consummate indoor plumbing (Table two). Thus, fifty-fifty if individuals are not experiencing the issue themselves, they may live in a community where incomplete plumbing is a serious issue.

Table 2 Estimates of elevated levels of water hardship in the Us.

Full size tabular array

The portion of the population affected by poor water quality is much greater than that of incomplete plumbing. Poor h2o quality in our analysis is indicated in two ways, (one) Safe Drinking Water Act Serious Violators and (ii) Make clean Water Act Significant Noncompliance. For the showtime, community water systems are regulated under the Safe Drinking Water Act and are scored based on their violation and compliance history, those community water systems that are the most problematic are recorded as Serious Violators by the Ecology Protection Agency²⁷. Second, any facility that discharges direct into waters in the U.s. is issued a Clean Water Act allow. Those which "concur a more than severe level of environmental threat" are ruled every bit being in Significant Noncompliance²⁷.

Using these ii measures of poor water quality, we discover 2.44% of customs water systems, a total of 1165, were Safe Drinking H2o Act Serious Violators and 6.01% of all Clean Water Act permittees, a full of 21,035, were in Significant Noncompliance every bit of xviii August 2020. At the canton level, this corresponds to an average of 2.86% of canton customs water systems being listed every bit Safe Drinking H2o Act Significant Violators and an boilerplate of 9.00% of canton Make clean Water Act permittees being listed equally Significant Noncompliers. Due to limitations in the data, we are unable to determine exactly how many individuals are linked to each problematic community water system or Make clean H2o Deed permittee, withal, we practice observe that over 81 one thousand thousand Americans live in counties where >1% of community water systems are listed equally Meaning Violators, and 217 million Americans live in counties where >one% of Clean Water Act permittees are Significant Noncompliers. Thus, although the number of individuals impacted past these issues is certainly far smaller than these totals, a vast number of Americans alive in communities where problems of h2o quality are elevated.

When looking at the issue spatially, nosotros tin see that while water hardship affects all parts of the land to some degree, the problems are clustered in space (Figs. 1–3). Chiefly, the clustering varies between each h2o issue. Incomplete plumbing is clustered in the 4 Corners, Alaska, Puerto Rico, the borderlands of Texas, and parts of Appalachia (Fig. 1); Safe Drinking Water Act Serious Violators are clustered in Appalachia, New United mexican states, Alaska, Puerto Rico, and the Northern Intermountain West (Fig. 2); and Clean Water Human activity Significant Noncompliance clearly follows state boundaries—likely speaking to variable monitoring past state—and is clustered in Washington, the Intermountain W, the Upper Midwest, Appalachia, and the lower Mississippi (Fig. three).

**Fig. 1: Map of the pct of county households without full indoor plumbing every bit reported by the 2014–2018 American Community Survey.**

**Fig. ii: Map of the percent of active county community water systems listed every bit Condom Drinking H2o Act (SDWA) Serious Violators.**

**Fig. iii: Map of the pct of county Clean Water Act (CWA) permittees listed as Clean Water Human activity Significant Noncompliers.**

Water injustice modeling

Although we can easily run across clustering past space in Figs. 1 through iii, the maps do not tell us whether or not incomplete plumbing and poor water quality are as well clustered by social dimensions, which would represent an environmental injustice. To assess this social clustering, nosotros approximate linear probability models of elevated levels of incomplete plumbing and poor water quality with the previously identified ecology justice dimensions of age, income, poverty, race, ethnicity, instruction, and rurality as our contained variables. We include these contained variables due to their prevalence within prior work on environmental injustice in both rural and urban areas^{17,eighteen,19,20,21,22,23,24,25}. Further, although there is not a one-to-one overlap, these variables conceptually map onto the dimensions of the Eye for Disease Control Social Vulnerability Index: Socioeconomic Status (i.eastward. income, poverty, educational activity), Household Composition & Disability (i.e. age), Minority Condition & Language (i.due east. race and ethnicity), and Housing & Transportation (i.e. rurality)²⁸.

For each outcome, nosotros beginning estimate purely descriptive models with simply one dimension of injustice included at a time, and so approximate a total model with all dimensions included. The outcomes are dichotomous measures of whether or not a canton had >1% of households with incomplete plumbing, >one% of customs h2o systems listed as Serious Violators, or >ane% of Clean H2o Act permittees in Pregnant Noncompliance. All descriptive statistics for the dichotomous outcomes are presented in Tabular array 1. Descriptive statistics for the continuous independent variables are presented in Supplementary Information (Supplementary Table i). Here we present the outcomes of the purely descriptive models visually in Fig. four and discuss the full models in the narrative. Full regression results, including verbal 95% confidence intervals and p-values, for all models are available in Supplementary Data (Supplementary Tables 2 and three).

**Fig. iv: Coefficient plot of descriptive regression model results.**

We notice elevated levels of incomplete plumbing at the canton level were significantly (p < 0.05) associated with older populations, lower income, college poverty, greater portions of ethnic people (American Indian, Alaska Natives, Native Hawaiian, and Other Pacific Islanders), lower levels of didactics, and more rural counties (Fig. 4). A great bargain of these associations persisted in a full model with all dimensions of injustice (Supplementary Table 2). The merely differences between the full model and the serial of purely descriptive models were that income, percent with at least a bachelor's caste, and non-metropolitan metropolitan adjacency were no longer significantly associated with elevated levels of incomplete plumbing. This indicates that the inequalities in plumbing access along the dimensions of historic period, poverty, indigeneity, low education, and farthermost rurality persist at the county level, fifty-fifty when bookkeeping for the other dimensions of environmental injustice.

The models for elevated levels of Safety Drinking Water Act Serious Violators indicated less social inequality than the models for incomplete plumbing. The purely descriptive models found elevated levels of Serious Violators were associated with higher income, higher poverty, and metropolitan counties (Fig. 4). The full model had minor variation, with median household income no longer existence meaning in the model (Supplementary Table 3). Thus, the total model shows that the association betwixt elevated levels of Serious Violators and higher poverty and metropolitan status persists even when considering other social dimensions.

We see the fewest indicators of water injustice for elevated levels of Clean Water Deed Meaning Noncompliance. In the purely descriptive models, we find older populations, less educated counties, and remote rural counties were significantly less likely to have elevated levels of noncompliance (Fig. 4). In the full model, the association for educational activity is no longer significant but age and rurality remain. Farther, in the total model nosotros find a significant association for percent Latino/a—where elevated levels of Significant Noncompliance were less likely in more Latino/a counties—that we did non discover in the purely descriptive models.

Give-and-take

Our findings demonstrate that the problem of water hardship in the U.s.a. is hidden, merely not rare. Indeed, millions live in counties where more than 1 out of 100 occupied households lack consummate plumbing. Millions more than live in places with chronic Prophylactic Drinking H2o Deed violations and Clean H2o Act noncompliance. We nowadays this paper to help sound the alarm of this significant household water crisis in the United States. Although the relative share of Americans experiencing this problem is low, the absolute number of people dealing with incomplete plumbing—a full of 489,836 households—and poor water quality—1165 community water systems and 21,035 Make clean Water Act permittees—remains quite high. Further, given the water infrastructure of the United States, consistently deemed as poor by experts^6,11, if action is non taken the state of affairs may just become worse.

These findings are fifty-fifty more apropos when considering that water hardship is spread unevenly beyond both space and society, reflecting the spatial patterning of social inequality due to settler colonialism, racism, and economic inequality in the Us. Figures one, 2, and 3 document the clear regional clustering of these issues and our models of environmental injustice demonstrate the social inequalities found for this class of hardship. Particularly in the case of incomplete plumbing, we find pregnant environmental injustice at the county level along the social dimensions of age, income, poverty, indigeneity, instruction, and rurality. These associations certainly stem from multiple causal pathways—for case associations with indigeneity likely stem from legacies of injustice besides as ongoing policies placing limitations on land use and infrastructure development on American Indian reservations¹⁵. Remedying these injustices will require careful attention to the root causes of the problem. That said, it is important to note that the signs of injustice for poor water quality were less clear than for incomplete plumbing, with far fewer significant associations. These differences between dimensions of water hardship highlight the nuance between each of these specific forms of h2o hardship, and suggest a ane-size-fits-all approach to remedying this crisis is unlikely to be effective. This demand for identify-based policy is made stark when nosotros view the obvious state level differences in Make clean Water Deed Significant Noncompliance in Fig. iii. A articulate direction for time to come piece of work is to investigate the crusade of these notable state-level differences.

The household water admission and quality crisis we take identified here is solvable. Policy is needed to specifically address these bug and bring this trouble into the spotlight. However, as indicated past the persistently high levels of Condom Drinking Water Act Serious Violation and Clean Water Act Pregnant Noncompliance, any policy put in identify must be enforceable and strong. As information technology currently stands, counties with elevated levels of incomplete plumbing and poor h2o quality in America—which are variously probable to exist more indigenous, less educated, older, and poorer—are standing to slip through the cracks.

Methods

Data sources

Data for this assay were extracted from the American Community Survey (ACS) five-year estimates for 2014–2018 via Integrated Public Use Microdata Series – National Historic Geographic information System (IPUMS-NHGIS)²⁶, and from the Environmental Protection Bureau's (EPA) Enforcement and Compliance History Online (Repeat) Exporter²⁷. Data were extracted at the canton level for all l states, Washington DC, and Puerto Rico. The ACS is an ongoing survey of the United states of america which documents a broad variety of social statistics ranging from simple population counts to housing characteristics. Due to the staggered sampling structure of the ACS, it takes 5 years for every canton to exist sampled. Because of this, researchers must use 5-year intervals to ensure complete information coverage. The data from these 5 years are projected into estimates for all counties in the United States for the 5-year menstruum in question. As of this study, 2014–2018 was the most recently available information.

Echo collates information from EPA-regulated facilities across the Us to report compliance, violation, and penalty data for all facilities for the virtually recent five-year interval. Echo data is updated weekly and the information for this newspaper was extracted on 18 August 2020. This ways that the data in our assay represents the condition of each community water arrangement or Clean Water Human action permittee, as reported by the EPA, equally of xviii August 2020. Only those community water systems or Clean H2o Act permittees listed as Active by ECHO were included in this analysis. Every bit ECHO data is at the level of the water system, permittee, or utility, nosotros aggregated data up to the canton level.

Safe Drinking Water Act data was geolocated using QGIS 3.10 based upon latitude and longitude. This was washed because other geographic identifiers for the Safe Drinking H2o Human activity information were often missing. In line with prior work^4,5,seven,8, and in order to facilitate a cleaner dataset, we simply focus on those water systems labeled community water systems for our analysis. Community water systems were geolocated based upon the county in which their latitude and longitude were located, if a customs water organisation had breadth and longitude over water, a nearest neighbor join was used. In full, 1334 out of 49,479 customs water systems were dropped because of in that location beingness no reported breadth or longitude. Of these, a full of four.0%, or 54 community waters systems, were reported as in serious violation.

Active Clean Water Act permittees were beginning identified by listed county. This was washed because 345,176 out of 350,476 permittees had a county reported. Those without a county reported were located using latitude and longitude in the same manner as community water systems. There were x permittees without latitude and longitude or county listed which were excluded from our analysis. Of these, seven were in significant noncompliance and three were not. Due to some Clean Water Act permittees having breadth and longitude placements far away from the United States, those over 100 km from their nearest county were excluded from analysis. Finally, for community water systems and Clean Water Deed permittees, some counties (76 for community water systems and 13 for Clean H2o Act permittees) had no reported cases. Those counties were treated as zeroes for cartography and as missing for modeling purposes.

Similar to prior work in this area^iv,5,viii, we restrict our analysis to the scale of the county for reasons related to data limitations and resulting conceptual validity. Although counties are arguably larger in geographic area than platonic for an environmental injustice analysis, if we were to utilise a smaller unit for which data is bachelor such as the demography tract, the conceptual validity of the analysis would exist limited due to the apolitical nature of these units. As outlined above, ECHO data is messy and missing many geographic identifiers. What is provided is more often than not either the canton or breadth and longitude. If only the county is provided, then nosotros are constrained to using the county regardless of conceptual validity. However, even when breadth and longitude are provided—which is the case for many observations—the provided point location says nothing about which households the water system or permittee serves or impacts. Due to this, whatever geographic unit we utilise carries the supposition that those in the unit could exist plausibly impacted by the water system or permittee. Given that counties are often responsible for both regulating drinking water, as well as maintaining and providing water infrastructure²⁹, we were comfortable with this assumption betwixt betoken location and presumed spatial impact when using the calibration of the county. All the same, we believe this assumption would have been invalid and untestable for smaller apolitical units for which demographic data is available such as census tracts.

Beyond the issues presented by ECHO information, the canton is too the advisable scale of analysis for this study due to the estimate-based nature of the ACS. ACS estimates are based on a rolling v-year sample structure and oft have very big margins of error. At the census tract level, these standard errors can be massive, particularly in rural areas^xxx,31,32. Due to this variation, and the need to include all rural areas in this assay, the county, where the margins of error are considerably smaller, is the appropriate unit for this written report. All of this said, the county is, in fact, a larger unit of measurement than ofttimes desired or used in environmental justice studies. Studies focused on exclusively urban areas with clearer pathways of impact tin and should utilise smaller units such as census tracts. It will be imperative for hereafter scholarship focused on water hardship across the rural-urban continuum to proceeds admission to reliable data on sub-county political units, as well every bit information linking h2o systems to users, to continue documenting and pushing for water justice.

Dependent variables

The dependent variables for this analysis were assessed in both a continuous and dichotomous format. For descriptive results and mapping, continuous measures were used. For models of h2o injustice, a dichotomous mensurate which classified counties as either having low levels of the specific water issue or elevated levels or the specific water issue, was used due to the low relative frequency of h2o admission and quality bug relative to the whole United States population. For all three outcomes, nosotros criterion an elevated level of the issue as what would exist viewed as an unacceptable level nether Un Sustainable Evolution Goal six.1, which states, "by 2030 attain universal and equitable access to rubber and affordable drinking water for all"¹. As this goal focuses on ensuring all people have rubber water, we deem a county as having an elevated level of the issue if >i% of households, customs water systems, or permittees had incomplete plumbing, were in Significant Violation, or Pregnant Noncompliance, respectively. Although we could have used an fifty-fifty stricter threshold given the SDG'southward emphasis on ensuring access for all people, we use 1% as our cut-off due to its nominal value and ease of interpretation.

For water access, the continuous measure was the percentage of households in a canton with incomplete household plumbing as reported past the ACS. The ACS currently asks respondents if they have access to hot and cold water, a sink with a faucet, and a bath or shower. Upwardly until 2016, the question besides included a flush toilet³³. As nosotros must utilise the most recent 2014–2018 5-year estimates to establish total coverage of all counties, this means that incomplete plumbing in this item may, or may not include a flush toilet depending on when the specific county was sampled. The dichotomous version of this variable benchmarked elevated levels of incomplete plumbing equally whether or not i% or more of households in a county had incomplete plumbing.

Water quality was assessed via both community water systems from the Safety Drinking H2o Human action, and from let data via the Clean Water Act. For Prophylactic Drinking Water Deed data, the continuous measure was the percentage of community water systems inside a county classified every bit a Safe Drinking H2o Act Serious Violator at fourth dimension of information extraction. The EPA assigns signal values of either 1, v, or ten based upon the severity of violations of the Safe Drinking H2o Act. A Serious Violator is i who has "an aggregate score of at least eleven points as a result of some combination of: unresolved more than serious violations (such as maximum contaminant level violations related to acute contaminants), multiple violations (health-based, monitoring and reporting, public notification and/or other violations), and/or continuing violations"²⁷. The dichotomous measure benchmarked elevated rates of Safe Drinking Water Act Significant Violation as whether or non >one% of county customs water systems were classified as Serious Violators.

For Make clean Water Human activity permit data, the continuous mensurate was the percent of let holders listed every bit in Significant Noncompliance at the fourth dimension of data extraction. Significant Noncompliance in the Make clean H2o Act refers to those permit holders who may pose a "more severe level of environmental threat" and is based upon both pollution levels and reporting compliance²⁷. The dichotomous measure once again set the threshold for elevated levels of poor h2o quality at whether or not >ane% of Clean H2o Human action permittees in a county were listed as in Significant Noncompliance at time of data extraction.

Independent variables

The contained variables we include in models of water injustice are those ofttimes shown to be related to environmental injustice in the U.s.a.. These include age, income, poverty, race, ethnicity, education, and rurality^{17,18,19,20,21,22,23,24,25}. Historic period was included every bit median historic period. Income was included as median household income. Poverty was the poverty rate of the county as adamant by the official poverty measure of the United States³⁴. Race and ethnicity was included as per centum non-Latino/a Black, per centum non-Latino/a indigenous, and pct Latino/a. Because the focus was on indigeneity, percent American Indian or Alaska Native was collapsed with Native Hawaiian or Other Pacific Islander. We did non include percent non-Latino/a white due to issues of multicollinearity. Finally, rurality was included every bit a iii-category county indicator of metropolitan, non-metropolitan metropolitan-adjacent, and not-metropolitan remote, as determined past the Office of Management and Budget in 2010³⁵. The OMB determines a county is metropolitan if information technology has a cadre urban area of 50,000 or more people, or is continued to a core metropolitan county by a 25% or greater share of commuting³⁵. A non-metropolitan canton is simply any canton not classified as metropolitan. Not-metropolitan metropolitan adjacent counties are those which immediately border a metropolitan county, and not-metropolitan remote counties are those that do not.

H2o injustice modeling approach

H2o injustice was assessed by estimating linear probability models for the iii dichotomous outcome variables with state stock-still effects to command for the visible state level heterogeneity and differences in policy, reporting, and enforcement (e.g. the clear state boundary effects in Fig. 3). We employ cluster-robust standard errors at the land level to account for both heteroskedasticity and state similarities. All modeling was performed in Stata 16.0 and mapping was performed in QGIS three.ten. We assessed all full models for multicollinearity via condition index and VIF values and the independent variables had an acceptable condition index of v.48, well below the conservative cutting-off of 15, equally well as VIF values of <10. Nosotros initially included percent non-Latino/a white as an independent variable, but removed the item due to unacceptably high condition index levels (>20). All indications of statistical significance are at the p < 0.05 level and 95% conviction intervals and verbal p-values of all estimates are provided in Supplementary Information. Each dependent variable was analyzed through a series of six models. First, we estimated separate purely descriptive models, where the only independent variables included were those associated with that specific dimension and the land fixed effects, for all five dimensions of environmental injustice. After estimating these 5 models, we estimated a total model including all social dimensions at once.

The reason for this approach was to ensure that nosotros provided a robust descriptive understanding of the on-the-ground social patterns of h2o hardship, in improver to a full model showing the strongest social correlates of this consequence. For example, if when we but included income variables we found that incomplete plumbing is less likely in counties with higher median incomes, but this effect goes abroad when we include other social variables, this does non remove the fact that there is an unequal distribution of incomplete plumbing by income on-the-footing. All that it means is that this income effect does not persist over and above the other social dimensions of environmental injustice. It may be that once other dimensions such as structural racism, captured by race and ethnicity variables, are considered, income is no longer a significant predictor. Nonetheless, at a pure associational level, incomplete plumbing would still be unequally distributed by income on-the-footing. In fact, this is exactly what we find for incomplete plumbing (Supplementary Tabular array 2). Due to this, both the pure descriptive and full models are needed for full understanding. Complete tables of all results are presented in the Supplementary Data File (Supplementary Tables ane through 4).

Reporting summary

Further data on research blueprint is available in the Nature Inquiry Reporting Summary linked to this commodity.

Data availability

The raw and geolocated datasets are publicly available on the Open up Science Framework project for this study at https://doi.org/10.17605/OSF.IO/ZPQR9 (https://osf.io/zpqr9/).

Code availability

Analysis lawmaking is available on the Open Science Framework projection for this report at https://doi.org/ten.17605/OSF.IO/ZPQR9 (https://osf.io/zpqr9/). As the raw data was not geolocated using a code-based functioning, lawmaking for this portion of the analysis is not available. However, the raw data is posted, and should researchers wish they will be able to use our description provided here to replicate geolocation using the GIS software of their pick. All other elements of the analysis are easily replicated via our provided code. Every bit the both the raw and geolocated datasets are provided, replication of our analysis should be straightforward.

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Acknowledgements

The authors would like to acknowledge Tom Dietz, Lauren Mullenbach, Matthew Brooks, and January Beecher for their feedback on this manuscript.

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Section of Sociology, Social Work, and Anthropology, Utah State University, Logan, UT, The states

J. Tom Mueller
Section of Folklore, Michigan State Academy, East Lansing, MI, The states

Stephen Gasteyer

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Conceptualization: J.T.Grand. and S.One thousand.; methodology: J.T.Yard.; formal analysis: J.T.M.; data curation: J.T.M.; writing- original draft preparation: J.T.M. and S.M.; writing – review and editing: J.T.M. and South.G.; visualization: J.T.M.

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Correspondence to J. Tom Mueller.

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Mueller, J.T., Gasteyer, Due south. The widespread and unjust drinking water and clean water crisis in the United States. Nat Commun 12, 3544 (2021). https://doi.org/10.1038/s41467-021-23898-z

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Received: 05 November 2020
Accepted: 19 May 2021
Published: 22 June 2021
DOI : https://doi.org/x.1038/s41467-021-23898-z

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