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This dataset contains tabular data at three scales (city, tract, and synoptic site) and related vector shapefiles (for watersheds or buffers around synoptic sites) for areas included in the Carbon in Urban River Biogeochemistry Project (CURB) to assess how social, built, and biophysical factors shape aquatic functions. The city scale included 486 urban areas in the continental United States with greater than 50,000 residents. Tabular data are provided for each urban area (CURB_CensusUrbanArea.csv) and all U.S. Census tracts within seven urban areas (Atlanta, GA, Boston, MA, Miami, FL, Phoenix, AZ, Portland, OR, Salt Lake City, UT, and San Francisco, CA; CURB_CensusTract.csv) to characterize a range of social, built, and biophysical factors. In six focal cities (Baltimore, MD, Boston, MA, Atlanta, GA, Miami, FL, Salt Lake City, UT, and Portland, OR) up to 100 sites were selected for synoptic water quality sampling. For each synoptic site tabular data (CURB_SynopticSite.csv) are provided to characterize a range of social, built, and biophysical factors within the watershed (Atlanta, Baltimore, Boston, Portland, Salt Lake City) or within a buffer of the site (Miami). Vector shapefiles are provided for the watershed boundaries (CURB_Synoptic_Watersheds.zip) for all synoptic sites in each city except Miami, FL where 400-m buffers (CURB_Miami_Synoptic_Buffers.zip) around the synoptic site were used. 

Abstract Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC‐MS or LC‐MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2^ndderivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co‐elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L⁻¹were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L⁻¹), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3–10.1 and 2.1–3.2 nmol L⁻¹, respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC‐MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method.