This study quantitatively reviews the hedonic literature examining surface water quality to assess how attributes of the commodity, housing market, and methodological choices lead to variation in the significance and expected sign of the estimated property value effects (i.e., elasticities). We conduct a meta-analysis of 29 studies with 290 unique estimates, published or released between 1985 and 2017, and find evidence based on probit meta-regression models that some of the definitions and decisions made in primary studies do influence the estimated relationship between water quality and home prices. Our most robust evidence suggests that methodological choices (e.g., accounting for spatial dependence, or if the water quality measure was based on something other than in situ measurement) have a critical role in determining the likelihood of finding a significant and theoretically expected result; and perhaps most importantly, it is not always selections that reflect best practices that lead to this finding. This study can help identify potential concerns with data and modeling choices in the collective hedonic literature focused on water quality.
Housing , Water Quality , Spatial Analysis
Using the US EPA's Grants Reporting and Tracking System (GRTS), we test if completion of best management practices (BMPs) through the Clean Water Act Section (§)319 National Nonpoint Source Program was associated with a decreasing trend in total suspended solids (TSS) load (metric tons/year). The study area chosen had 21 completed projects in the Cuyahoga River watershed in northeastern Ohio from 2000 to 2018. The §319 projects ranged from dam removal, floodplain/wetland restoration to stormwater projects. There was an overall decreasing trend in TSS loads. We identified three phases of project implementation and completion, where phase 1 had ongoing projects, but none completed (2000-2004). The steepest decrease in loads, identified as phase 2 (2005-2011), was associated with completion of low-head dam modification and removal projects on the mainstem of the Cuyahoga River. A likely decreasing trend was associated with projects completed in the tributaries, such as natural channel design restoration and stormwater green infrastructure (phase 3). Pairing sediment reduction estimates from projects with the river's flow normalized TSS loading trend, we estimated that the §319 effort may account for a small fraction of the TSS load reduction. Other stream restoration projects (non-§319) have also been done in the Cuyahoga watershed by other organizations. However, trying to compile these other projects is challenging in larger watersheds having multiple municipalities, agencies, and nonprofits doing restoration without better coordinated record keeping and monitoring. While a decreasing trend in a pollutant load is a desirable water quality outcome, determining what contributed to that trend remains difficult.
Intrinsically disordered proteins (IDPs) are important for a broad range of biological functions and are involved in many diseases. An understanding of intrinsic disorder is key to develop compounds that target IDPs. Experimental characterization of IDPs is hindered by the very fact that they are highly dynamic. Computational methods that predict disorder from the amino acid sequence have been proposed. Here, we present ADOPT (Attention DisOrder PredicTor), a new predictor of protein disorder. ADOPT is composed of a self-supervised encoder and a supervised disorder predictor. The former is based on a deep bidirectional transformer, which extracts dense residue-level representations from Facebook's Evolutionary Scale Modeling library. The latter uses a database of nuclear magnetic resonance chemical shifts, constructed to ensure balanced amounts of disordered and ordered residues, as a training and a test dataset for protein disorder. ADOPT predicts whether a protein or a specific region is disordered with better performance than the best existing predictors and faster than most other proposed methods (a few seconds per sequence). We identify the features that are relevant for the prediction performance and show that good performance can already be gained with <100 features. ADOPT is available as a stand-alone package at https://github.com/PeptoneLtd/ADOPT and as a web server at https://adopt.peptone.io/.
We construct a comprehensive, publicly-available meta-dataset based on 36 hedonic studies that examine the effects of water quality on housing values in the United States. The meta-dataset includes 656 unique estimates and entails a cluster structure that accounts for price effects at different distances. Focusing on water clarity, we estimate reduced-form meta-regressions that account for within-market dependence, statistical precision, housing market and waterbody heterogeneity, publication bias, and methodological practices. While we find evidence of systematic heterogeneity, the out-of-sample transfer errors are large. We discuss the implications for benefit transfer and future work to improve transfer performance.
We estimate a cost function for a water treatment plant in Ohio to assess the avoided-treatment costs resulting from improved source water quality. Regulations and source water concerns motivated the treatment plant to upgrade its treatment process by adding a granular activated carbon building in 2012. The cost function uses daily observations from 2013 to 2016; this allows us to compare the results to a cost function estimated for 2007-2011 for the same plant. Both models focus on understanding the relationship between treatment costs per 1,000 gallons (per 3.79 m3) of produced drinking water and predictor variables such as turbidity, pH, total organic carbon, deviations from target pool elevation, final production, and seasonal variables. Different from the 2007-2011 model, the 2013-2016 model includes a harmful algal bloom toxin variable. We find that the new treatment process leads to a different cost model than the one that covers 2007-2011. Both total organic carbon and algal toxin are important drivers for the 2013-2016 treatment costs. This reflects a significant increase in cyanobacteria cell densities capable of producing toxins in the source water between time periods. The 2013-2016 model also reveals that positive and negative shocks to treatment costs affect volatility, the changes in the variance of costs through time, differently. Positive shocks, or increased costs, lead to higher volatility compared to negative shocks, or decreased costs, of similar magnitude. After quantifying the changes in treatment costs due to changes in source water quality, we discuss how the study results inform policy-relevant decisions.
For community water providers, safeguarding source waters from contamination offers an additional barrier of protection and a potential means of avoiding in-plant treatment costs. Whether source water protection efforts are cost-effective relative to in-plant treatment requires hydrologic, geologic, and climatologic knowledge of source watersheds, as well as an understanding of how changes in source water quality affect treatment costs. Quantitative evidence on the latter relationship is limited. This study estimates separate hedonic cost functions for water systems that primarily use surface water sources and those that primarily use groundwater sources using a database of United States (US) Community Water Systems. Cost functions relate annual variable treatment cost to production, factor input prices, capital stock, and source water quality, as proxied by land use within various ex-ante defined contributing areas (i.e., surrounding land areas affecting source water quality). For surface water systems, a 1% increase in urban land relative to forestland is correlated with a 0.13% increase in annual variable treatment costs. In this analysis, the relationship between costs and agricultural land is not statistically significant. Conversely, for groundwater systems, a 1% increase in agricultural land relative to forestland is correlated with a 0.24% increase in costs, whereas in this analysis the relationship between costs and urban land is not statistically significant. The cost-effectiveness of forestland preservation, based on sample means, varies considerably with the size of the contributing area, with no clear indication as to whether preservation is more likely to be cost-effective for surface water or groundwater systems.
Watershed protection, and associated in situ water quality improvements, has received considerable attention as a means for mitigating health risks and avoiding expenditures at drinking water treatment plants (DWTPs). This study reviews the literature linking source water quality to DWTP expenditures. For each study, we report information on the modeling approach, data structure, definition of treatment costs and water quality, and statistical methods. We then extract elasticities indicating the percentage change in drinking water treatment costs resulting from a 1% change in water quality. Forty-six elasticities are obtained for various water quality parameters, such as turbidity, total organic carbon (TOC), nitrogen, sediment loading, and phosphorus loading. An additional 29 elasticities are obtained for land use classification (e.g., forest, agricultural, urban), which often proxy source water quality. Findings indicate relatively large ranges in the estimated elasticities of most parameters and land use classifications. However, average elasticities are smaller and ranges typically narrower for studies that incorporated control variables consistent with economic theory in their models. We discuss the implications of these findings for a DWTP's incentive to engage in source water protection and highlight gaps in the literature.
Best management practices (BMPs) for reducing agricultural non-point source pollution are widely available. However, agriculture remains a major global contributor to degradation of waters because farmers often do not adopt BMPs. To improve water quality, it is necessary to understand the factors that influence BMP adoption by farmers. We review the findings of BMP adoption studies from both developed and developing countries, published after (or otherwise not included in) two major literature reviews from 2007 and 2008. We summarize the study locations, scales, and BMPs studied; the analytical methods used; the factors evaluated; and the directionality of each factor's influence on BMP adoption. We then present a conceptual framework for BMP adoption decisions that emphasizes the importance of scale, the tailoring or targeting of information and incentives, and the importance of expected farm profits. We suggest that future research directions should focus on study scale, on measuring and modeling of adoption as a continuous process, and on incorporation of social norms and uncertainty into decision-making. More research is needed on uses of social media and market recognition approaches (such as certificate schemes and consumer labeling) to influence BMP adoption.
Water quality trading (WQT) has potential to be a low-cost means for achieving water quality goals. WQT allows regulated wastewater treatment plants (WWTPs) facing discharge limits the flexibility to either reduce their own discharge or purchase pollution control from other WWTPs or nonpoint sources (NPSs) such as agricultural producers. Under this limited scope, programs with NPSs have been largely unsuccessful at meeting water quality goals. The decision to participate in trading depends on many factors including the pollution control costs, uncertainty in pollution control, and discharge limits. Current research that focuses on making WQT work tends to identify how to increase participation by traditional traders such as WWTPs and agricultural producers. As an alternative, but complementary approach, we consider whether augmenting WQT markets with non-traditional participants would help increase the number of trades. Determining the economic incentives for these potential participants requires the development of novel benefit functions requiring not only economic considerations, but also accounting for ecological and engineering processes. Existing literature on non-traditional participants in environmental markets tends to center on air quality and only increasing citizen participation as buyers. Here, we consider the issues for broadening participation (both buyers and sellers) in WQT and outline a multidisciplinary approach to begin evaluating feasibility.
DARPin libraries, based on a Designed Ankyrin Repeat Protein consensus framework, are a rich source of binding partners for a wide variety of proteins. Their modular structure, stability, ease of in vitro selection and high production yields make DARPins an ideal starting point for further engineering. The X-ray structures of around 30 different DARPin complexes demonstrate their ability to facilitate crystallization of their target proteins by restricting flexibility and preventing undesired interactions of the target molecule. However, their small size (18 kDa), very hydrophilic surface and repetitive structure can limit the DARPins' ability to provide essential crystal contacts and their usefulness as a search model for addressing the crystallographic phase problem in molecular replacement. To optimize DARPins for their application as crystallization chaperones, rigid domain-domain fusions of the DARPins to larger proteins, proven to yield high-resolution crystal structures, were generated. These fusions were designed in such a way that they affect only one of the terminal capping repeats of the DARPin and do not interfere with residues involved in target binding, allowing to exchange at will the binding specificities of the DARPin in the fusion construct. As a proof of principle, we designed rigid fusions of a stabilized version of Escherichia coli TEM-1 ß-lactamase to the C-terminal capping repeat of various DARPins in six different relative domain orientations. Five crystal structures representing four different fusion constructs, alone or in complex with the cognate target, show the predicted relative domain orientations and prove the validity of the concept.
Ankyrin Repeat , Crystallography, X-Ray/methods , Proteins/chemistry , Amino Acid Sequence , Crystallization , Escherichia coli/enzymology , Escherichia coli/metabolism , Green Fluorescent Proteins/metabolism , Maltose-Binding Proteins/chemistry , Molecular Chaperones/chemistry , Molecular Sequence Data , Protein Binding , Protein Engineering/methods , Protein Folding , Protein Structure, Secondary , Protein Structure, Tertiary , Recombinant Fusion Proteins/chemistry , Sequence Homology, Amino Acid , beta-Lactamases/chemistry
This paper presents the data sources and methodology used to estimate Green Net National Product (GNNP), an economic metric of sustainability, for Puerto Rico. Using the change in GNNP as a one-sided test of weak sustainability (i.e., positive growth in GNNP is not enough to show the economy is sustainable), we measure the movement away from sustainability by examining the change in GNNP from 1993 to 2009. In order to calculate GNNP, we require both economic and natural capital data, but limited data for Puerto Rico require a number of simplifying assumptions. Based on the environmental challenges faced by Puerto Rico, we include damages from air emissions and solid waste, the storm protection value of mangroves and the value of extracting crushed stone as components in the depreciation of natural capital. Our estimate of GNNP also includes the value of time, which captures the effects of technological progress. The results show that GNNP had an increasing trend over the 17 years studied with two periods of negative growth (2004-2006 and 2007-2008). Our additional analysis suggests that the negative growth in 2004-2006 was possibly due to a temporary economic downturn. However, the negative growth in 2007-2008 was likely from the decline in the value of time, suggesting the island of Puerto Rico was moving away from sustainability during this time.
Conservation of Natural Resources , Environment , Environmental Pollution , Puerto Rico , Socioeconomic Factors
Pseudomonas species strain SBV1 can rapidly grow on medium containing ß-valine as a sole nitrogen source. The tertiary amine feature of ß-valine prevents direct deamination reactions catalyzed by aminotransferases, amino acid dehydrogenases, and amino acid oxidases. However, lyase- or aminomutase-mediated conversions would be possible. To identify enzymes involved in the degradation of ß-valine, a PsSBV1 gene library was prepared and used to complement the ß-valine growth deficiency of a closely related Pseudomonas strain. This resulted in the identification of a gene encoding ß-valinyl-coenzyme A ligase (BvaA) and two genes encoding ß-valinyl-CoA ammonia lyases (BvaB1 and BvaB2). The BvaA protein demonstrated high sequence identity to several known phenylacetate CoA ligases. Purified BvaA enzyme did not convert phenyl acetic acid but was able to activate ß-valine in an adenosine triphosphate (ATP)- and CoA-dependent manner. The substrate range of the enzyme appears to be narrow, converting only ß-valine and to a lesser extent, 3-aminobutyrate and ß-alanine. Characterization of BvaB1 and BvaB2 revealed that both enzymes were able to deaminate ß-valinyl-CoA to produce 3-methylcrotonyl-CoA, a common intermediate in the leucine degradation pathway. Interestingly, BvaB1 and BvaB2 demonstrated no significant sequence identity to known CoA-dependent ammonia lyases, suggesting they belong to a new family of enzymes. BLAST searches revealed that BvaB1 and BvaB2 show high sequence identity to each other and to several enoyl-CoA hydratases, a class of enzymes that catalyze a similar reaction with water instead of amine as the leaving group.
Ammonia-Lyases/metabolism , Coenzyme A/metabolism , Metabolic Networks and Pathways/genetics , Pseudomonas/genetics , Pseudomonas/metabolism , Valine/metabolism , Ammonia-Lyases/genetics , Gene Library , Genetic Complementation Test , Pseudomonas/growth & development , Sequence Homology , Substrate Specificity
Deciphering the structural features that functionally separate ammonia lyases from aminomutases is of interest because it may allow for the engineering of more efficient aminomutases for the synthesis of unnatural amino acids (e.g., ß-amino acids). However, this has proved to be a major challenge that involves understanding the factors that influence their activity and regioselectivity differences. Herein, we report evidence of a structural determinant that dictates the activity differences between a phenylalanine ammonia lyase (PAL) and aminomutase (PAM). An inner loop region that closes the active sites of both PAM and PAL was mutated within PAM (PAM residues 77-97) in a stepwise approach to study the effects when the equivalent residue(s) found in the PAL loop were introduced into the PAM loop. Almost all of the single loop mutations triggered a lyase phenotype in PAM. Experimental and computational evidence suggest that the induced lyase features result from inner loop mobility enhancements, which are possibly caused by a 310-helix cluster, flanking α-helices, and hydrophobic interactions. These findings pinpoint the inner loop as a structural determinant of the lyase and mutase activities of PAM.
Intramolecular Transferases/chemistry , Phenylalanine Ammonia-Lyase/chemistry , Phenylalanine Ammonia-Lyase/metabolism , Catalytic Domain , Crystallography, X-Ray , Intramolecular Transferases/genetics , Intramolecular Transferases/metabolism , Models, Molecular , Molecular Dynamics Simulation , Phenylalanine Ammonia-Lyase/genetics , Protein Conformation , Temperature
Ammonia lyases (AL) and aminomutases (AM) are emerging in green synthetic routes to chiral amines and an AL is being explored as an enzyme therapeutic for treating phenylketonuria and cancer. Although the restricted substrate range of the wild-type enzymes limits their widespread application, the non-reliance on external cofactors and direct functionalization of an olefinic bond make ammonia lyases attractive biocatalysts for use in the synthesis of natural and non-natural amino acids, including ß-amino acids. The approach of combining structure-guided enzyme engineering with efficient mutant library screening has extended the synthetic scope of these enzymes in recent years and has resolved important mechanistic issues for AMs and ALs, including those containing the MIO (4-methylideneimidazole-5-one) internal cofactor.
Ammonia-Lyases/chemistry , Drug Industry/methods , Industrial Microbiology/methods , Intramolecular Transferases/chemistry , Protein Engineering/methods , Bacterial Proteins/chemistry , Fungal Proteins/chemistry , Metabolic Networks and Pathways
This paper introduces a collection of four articles describing the San Luis Basin Sustainability Metrics Project. The Project developed a methodology for evaluating regional sustainability. This introduction provides the necessary background information for the project, description of the region, overview of the methods, and summary of the results. Although there are a multitude of scientifically based sustainability metrics, many are data intensive, difficult to calculate, and fail to capture all aspects of a system. We wanted to see if we could develop an approach that decision-makers could use to understand if their system was moving toward or away from sustainability. The goal was to produce a scientifically defensible, but straightforward and inexpensive methodology to measure and monitor environmental quality within a regional system. We initiated an interdisciplinary pilot project in the San Luis Basin, south-central Colorado, to test the methodology. The objectives were: 1) determine the applicability of using existing datasets to estimate metrics of sustainability at a regional scale; 2) calculate metrics through time from 1980 to 2005; and 3) compare and contrast the results to determine if the system was moving toward or away from sustainability. The sustainability metrics, chosen to represent major components of the system, were: 1) Ecological Footprint to capture the impact and human burden on the system; 2) Green Net Regional Product to represent economic welfare; 3) Emergy to capture the quality-normalized flow of energy through the system; and 4) Fisher information to capture the overall dynamic order and to look for possible regime changes. The methodology, data, and results of each metric are presented in the remaining four papers of the special collection. Based on the results of each metric and our criteria for understanding the sustainability trends, we find that the San Luis Basin is moving away from sustainability. Although we understand there are strengths and limitations of the methodology, we argue that each metric identifies changes to major components of the system.
Conservation of Natural Resources/methods , Environmental Monitoring/methods , Carbon Footprint , Colorado , Decision Making , Environment , Pilot Projects , Time Factors
This paper presents the data sources and methodology used to estimate Green Net Regional Product (GNRP), a green accounting approach, for the San Luis Basin (SLB). We measured the movement away from sustainability by examining the change in GNRP over time. Any attempt at green accounting requires both economic and natural capital data. However, limited data for the Basin requires a number of simplifying assumptions and requires transforming economic data at the national, state, and county levels to the level of the SLB. Given the contribution of agribusiness to the SLB, we included the depletion of both groundwater and soil as components in the depreciation of natural capital. We also captured the effect of the consumption of energy on climate change for future generations through carbon dioxide (CO(2)) emissions. In order to estimate the depreciation of natural capital, the shadow price of water for agriculture, the economic damages from soil erosion due to wind, and the social cost of carbon emissions were obtained from the literature and applied to the SLB using benefit transfer. We used Colorado's total factor productivity for agriculture to estimate the value of time (i.e., to include the effects of exogenous technological progress). We aggregated the economic data and the depreciation of natural capital for the SLB from 1980 to 2005. The results suggest that GNRP had a slight upward trend through most of this time period, despite temporary negative trends, the longest of which occurred during the period 1985-86 to 1987-88. However, given the upward trend in GNRP and the possibility of business cycles causing the temporary declines, there is no definitive evidence of moving away from sustainability.
Conservation of Natural Resources/methods , Environmental Monitoring/methods , Climate Change , Colorado , Environment , Models, Economic
Turn to switch: A mutant of phenylalanine aminomutase was engineered that can catalyze the regioselective amination of cinnamate derivatives (see scheme, red) to, for example, ß-amino acids. This regioselectivity, along with the X-ray crystal structures, suggests two distinct carboxylate binding modes differentiated by C(ß)-C(ipso) bond rotation, which determines if ß- (see scheme) or α-addition takes place.
Cinnamates/metabolism , Phenylalanine Ammonia-Lyase/metabolism , Phenylalanine/metabolism , Protein Engineering , Taxus/enzymology , Amination , Cinnamates/chemistry , Models, Molecular , Mutation , Phenylalanine/chemistry , Phenylalanine Ammonia-Lyase/chemistry , Phenylalanine Ammonia-Lyase/genetics , Stereoisomerism , Substrate Specificity , Taxus/chemistry , Taxus/genetics , Taxus/metabolism
