ArticleEnvironmental science & technology2014
Nitrate variability in groundwater of North Carolina using monitoring and private well data models.
Article in Environmental science & technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association of distance to swine concentrated animal feeding operations with immune-mediated diseases: An exploratory gene-environment study.Environment international · 2023Pooled it
- A review of geospatial exposure models and approaches for health data integration.Journal of exposure science & environmental epidemiology · 2025Review
- Evaluation of Bayesian Maximum Entropy Data Fusion Approaches to Estimate Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes and to Inform Epidemiological Analyses in the US Gulf States.Environmental science & technology · 2025Article
- A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target.The Science of the total environment · 2023Article
- Progression of a large syphilis outbreak in rural North Carolina through space and time: Application of a Bayesian Maximum Entropy graphical user interface.PLOS global public health · 2023Article
- Identifying sources of antibiotic resistance genes in the environment using the microbialFrontiers in microbiology · 2023Article
- Scalable penalized spatiotemporal land-use regression for ground-level nitrogen dioxide.The annals of applied statistics · 2021Article
- Sources and Risk Factors for Nitrate and Microbial Contamination of Private Household Wells in the Fractured Dolomite Aquifer of Northeastern Wisconsin.Environmental health perspectives · 2021Article
- Private Wells and Rural Health: Groundwater Contaminants of Emerging Concern.Current environmental health reports · 2020Review
- Seasonal Variation of Water Quality in Unregulated Domestic Wells.International journal of environmental research and public health · 2019Article
- Modeling groundwater nitrate exposure in private wells of North Carolina for the Agricultural Health Study.The Science of the total environment · 2019Article
- Drinking Water Nitrate and Human Health: An Updated Review.International journal of environmental research and public health · 2018Review
- Predicting nonpoint stormwater runoff quality from land use.PloS one · 2018Article
- Integrating remote sensing with nutrient management plans to calculate nitrogen parameters for swine CAFOs at the sprayfield and sub-watershed scales.The Science of the total environment · 2017Article
- Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA).The Science of the total environment · 2016Article
- Modeling groundwater nitrate concentrations in private wells in Iowa.The Science of the total environment · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Nitrate (NO3-) is a widespread contaminant of groundwater and surface water across the United States that has deleterious effects to human and ecological health. This study develops a model for predicting point-level groundwater NO3- at a state scale for monitoring wells and private wells of North Carolina. A land use regression (LUR) model selection procedure is developed for determining nonlinear model explanatory variables when they are known to be correlated. Bayesian Maximum Entropy (BME) is used to integrate the LUR model to create a LUR-BME model of spatial/temporal varying groundwater NO3- concentrations. LUR-BME results in a leave-one-out cross-validation r2 of 0.74 and 0.33 for monitoring and private wells, effectively predicting within spatial covariance ranges. Results show significant differences in the spatial distribution of groundwater NO3- contamination in monitoring versus private wells; high NO3- concentrations in the southeastern plains of North Carolina; and wastewater treatment residuals and swine confined animal feeding operations as local sources of NO3- in monitoring wells. Results are of interest to agencies that regulate drinking water sources or monitor health outcomes from ingestion of drinking water. Lastly, LUR-BME model estimates can be integrated into surface water models for more accurate management of nonpoint sources of nitrogen.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.