Grantee Research Project Results

Final Report: Valuation of Water Quality Change in Environment and Economy Context: Ecosystem Services across Gradients of Degradation and Local Economic Interest

EPA Grant Number: R836320
Title: Valuation of Water Quality Change in Environment and Economy Context: Ecosystem Services across Gradients of Degradation and Local Economic Interest
Investigators: Swallow, Stephen , Vadas, Timothy M. , Kirchhoff, Christine , Helton, Ashley , Liu, Pengfei
Institution: University of Connecticut
EPA Project Officer: Packard, Benjamin H
Project Period: August 1, 2016 through July 31, 2019 (Extended to July 31, 2023)
Project Amount: $799,994
RFA: Water Quality Benefits (2015) RFA Text | Recipients Lists
Research Category: Water

Objective:

The proposed research aims to value changes in water quality via a preference function model designed explicitly for calibration and adaptation to alternative study-sites. The work will address critical deficiencies with broad applicability and application of traditional benefit transfer following three specific objectives. First, we will measure the relative value of water quality investments and stream ecosystem restoration in sites across the spectrum of degradation. Second, we will measure how the value of water quality and ecosystem restoration is affected by the context of where the streams are relative to current and past economic activity, especially jobs in pollution intensive industries versus other employment. Third, based on these primary studies we will use measures of personal environmental attitudes, measures of ecosystem/degradation context, and measures of local economic context to develop a framework guiding the applicability for transfer of benefits to alternative sites not directly studied.

Summary/Accomplishments (Outputs/Outcomes):

Our research efforts consisted of four main components: (1) Site Selection and Sampling. (2) Focus Group, Survey Development, and Implementation. (3) Preliminary Analysis within the Study Site. (4) Benefit Transfer.

Site Selection and Sampling: We selected a geographically extensive region encompassing diverse ecological and socio-economic contexts. Our sampling approach targeted 20 counties with a representative cross-section of three critical indices: the Socioeconomic Index, the Ecological Integrity Index, and the Pollution Economy Index. These indices were computed for all counties within our study region. Using this data, we categorized all 215 selected counties into five distinct clusters, each designed to comprehensively cover our study area. Subsequently, we arrived at our final selection of 20 counties for our survey instrument by randomly drawing four counties from each cluster.

Focus Group, Survey Development, and Implementation: We conducted eleven focus group sessions at various locations and times, each featuring a unique format that evolved based on insights gained from previous sessions. Through these focus groups and interviews, we identified six key attributes along with their corresponding levels and presentation methods. These selected attribute levels were crafted to facilitate an assessment of water quality and trade-offs that are meaningful to the broader population.

Our data collection efforts encompassed two waves of Facebook Campaign, several waves of traditional Address-based Sampling involving email and postcard mailing, and two waves of the Qualtrics panel. In total, we gathered 7,030 valid responses from diverse sources. The majority of our data originated from Facebook, consisting of 3,259 responses spanning the years 2020 to 2021 and an additional 546 responses from 2023. Additionally, we received 317 responses through postal mail and email, indicating a more targeted and localized data collection approach. Finally, we leveraged the Qualtrics panel, a widely used online survey platform, to collect 2,908 responses.

Preliminary Analysis within the Study Site: The study's model results yielded several significant findings: (1) Respondents held a positive perception of moderately improving water quality but assigned negative or no value to enhancing severely degraded water quality. (2) There was a significant preference for improvements in biological conditions over ecosystem services. (3) Preferences for changes in both biological conditions and ecosystem service varied depending on the existing baseline conditions, emphasizing the importance of considering the initial status when assessing the perceived value of water quality improvements. (4) Geographical location also significantly influenced the perceived value of water quality improvement. (5) The variations in the three indices influenced the perceived value of water quality investments. (6) The environmental attitudes and pollution perception exhibited a notable relationship with respondents' utility for water quality improvement, with higher perceptions of water pollution and beliefs about their households contributing to pollution correlating with significantly positive utility for water quality enhancement. These findings underscore the complex interplay of factors in individuals' perceptions and valuation of water quality improvements.

Benefit Transfer: Initially, we conducted benefit transfer assessments for each of the 20 individual counties, and subsequently, we aggregated the data to perform our analysis within a statistically valid and representative cluster system. Following the methodology detailed by Morrison et al. (2002), we executed two distinct validity tests to assess the credibility of benefit transfer across the clustered areas. These tests assessed the equality of 1) the overall model and 2) the implicit price.

High test statistics values for the overall model clearly indicated the rejection of the null hypothesis, concluding that the two models were not equivalent. The analysis of benefit transfer validity in this study, using implicit pricing, yielded the following results: Regarding biological conditions, the findings showed a certain degree of overlap in confidence intervals for non-monetary environmental changes across all cluster-level data. Similar results were observed when examining non-monetary changes related to ecosystem services, with significant overlaps in the confidence intervals for different cluster-level samples. However, based on the t-test, the validity of the convergence hypothesis was accepted in 7 implicit price cases, while the remaining cases were rejected. Hence, the decision to accept or reject the null hypothesis remained uncertain. Benefit transfer based on different levels of the three indices exhibited very similar patterns.

Journal Articles:

No journal articles submitted with this report: View all 5 publications for this project

Supplemental Keywords:

Non-Market Valuation, Discrete Choice Experiment, Stated Preference, Water Quality

Relevant Websites:

UConn Water Quality and Land Cover Research Exit

Appendix Exit

Survey Package Exit

Dataverse Exit

Benefit Transfer Toolkit Exit

Progress and Final Reports:

Original Abstract

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.