Precipitation Chemistry Data Research Articles

Understanding the origins of and influences on precipitation major ion chemistry on the Island of O'ahu, Hawai'i.

Precipitation is the primary groundwater source for the Island of O'ahu, Hawai'i, USA, and is an important source of terrestrial nutrients. Since Pacific Islands are particularly vulnerable to the impacts of climate change, they are important venues for studying the controls on and fluctuations in precipitation chemistry. Spatial variations in some of the dissolved rainfall ions can also be of value as natural geochemical tracers in examining surface and groundwater flow. This study collected and chemically analyzed bulk precipitation from 20 sites across the Island of O'ahu approximately quarterly between April 2018 and August 2021. The new precipitation chemistry data were integrated with previously published precipitation data to characterize major ion composition and examine the atmospheric processes controlling inorganic ion deposition. Linear regression and multivariate analysis were used to quantify the relationships among major ions and to assess the impacts of various environmental and meteorological factors on precipitation chemistry. Ordinary kriging and inverse distance weighted interpolations were conducted to help visualize spatial variations in major ion deposition. The results clearly indicate that ocean sea spray is the primary driver of precipitation inorganic chemistry, with marine sea salt aerosols accounting for more than 90% of the measured ion load. However, they also show that various weather patterns and nutrient sources impact inorganic deposition. Most notably, upper atmospheric transport of Asian continental dust during Hawaiian wet seasons, Ca2+ from local sedimentary deposits, and anthropogenic K+ from agricultural activity appear to be substantial non-marine deposition sources. This study synthesizes data from multiple sources into the most spatially and topographically diverse precipitation collector network on O'ahu to date. The findings from this effort help establish a baseline for assessing future fluctuations in inorganic ion deposition and lay important groundwork for examining connections between precipitation and groundwater chemistry within the study area.

Chemical composition of monsoon bulk precipitation in the Salalah area, Oman

Precipitation chemistry data provide important information for environmental studies on large-scale element cycling and anthropogenic impacts on our atmosphere, but also for hydrochemical models and groundwater recharge estimations via the Chloride Mass Balance method. Such recharge data play a crucial role in groundwater management, particularly in (semi-)arid areas. Unfortunately, precipitation analyses are often scarce in such regions. This also applies to the Arabian Peninsula, including southern Oman. To overcome this lack of rain chemistry data, we developed a strategy for automatic weekly bulk precipitation sampling, using recently designed automatic rainwater samplers. The integral samples were gathered along an elevation gradient from the Salalah coast to the Dhofar mountains during the Indian Ocean Monsoon seasons 2017 and 2018.Our major ion analyses of the rainwater samples revealed considerable temporal and spatial heterogeneity, in terms of ion proportions and absolute concentrations. Samples from the coast were relatively salty (EC mostly >3000 μS cm−1) and rich in Na+ and Cl−, reflecting small rain amounts and a sea spray effect. Further inland, solute concentrations were lower, partly due to more precipitation, and ions such as Ca2+ and SO42− gained importance, probably due to calcite and gypsum dust. This pattern reflects the interplay between solute availability (influenced by regional geology, wind direction at different altitudes, and wind speed) and precipitation amounts. Cl−/Br− ratios were fairly uniform and scattered around the seawater value. Combining ion concentrations and rain amounts yielded bulk depositions that showed an erratic pattern along the elevation gradient, i.e., depositions did not decrease steadily in inland direction, as one may assume. This suggests that the occasionally reported approach of collecting a few opportunistic grab samples at a single site is unlikely to yield data that are representative for a larger coastal study area.

Impacts of Hurricanes on Nutrient Export and Ecosystem Metabolism in a Blackwater River Estuary Complex

Hurricanes have the ability to export uncharacteristically large amounts of nutrients from terrestrial systems into riverine and estuarine networks, altering rates of ecosystem metabolism throughout the aquatic continuum. In order to explore these impacts and compare these values to common precipitation events, water quality and chemistry data from the National Estuarine Research Reserve’s System Wide Monitoring Program (NERR-SWMP) were combined with discharge data from the United States Geological Survey (USGS) to calculate biogeochemical export from a Florida coastal blackwater river. This analysis was focused on the years 2016–2020, when Hurricanes Matthew, Irma, and Dorian impacted the landscape of Florida’s Atlantic coast. Hurricane Irma, the only hurricane to occur after especially wet summer conditions, dwarfed the other two hurricanes in the export of dissolved organic carbon (DOC), with an increase from <5 kg DOC day−1 to approximately 250 kg DOC day−1. Soluble reactive phosphorus (SRP) and most nitrogen species export exhibited similar trends. Additionally, other spikes in export occurred during non-hurricane months, and no significant differences between monthly export values were found between hurricane and non-hurricane months. However, net ecosystem metabolism (NEM) was calculated at similar intervals and revealed significantly lower NEM during months of hurricane passage. On monthly timescales, this work suggests that lower-category hurricanes might not significantly impact organic matter export, but the shortened export interval associated with hurricane impacts produces significant implications for NEM.

An R Package for Generating Covariance Matrices for Maximum-Entropy Sampling from Precipitation Chemistry Data

We present an open-source R package (MESgenCov v 0.1.0) for temporally fitting multivariate precipitation chemistry data and extracting a covariance matrix for use in the MESP (maximum-entropy sampling problem). We provide multiple functionalities for modeling and model assessment. The package is tightly coupled with NADP/NTN (National Atmospheric Deposition Program/National Trends Network) data from their set of 379 monitoring sites, 1978–present. The user specifies the sites, chemicals, and time period desired, fits an appropriate user-specified univariate model for each site and chemical selected, and the package produces a covariance matrix for use by MESP algorithms.

The precipitation chemistry and acidity over China during 2018

This paper reports the acid rain observation data from 376 Acid Rain Monitoring stations and the precipitation chemistry data from 5 Global Atmosphere Watch stations of China Meteorological Administration(CMA) during 2018. The variation characteristics of acid rain in China and that of precipitation chemistry in Eastern China are discussed. The results show that the acid rain area in China is mainly distributed in the Southeast and South of China and dispersively in North and Southwest of China. Heavy acid rain area is only limited in Eastern part of Hunan province. The annual mean precipitation pH value of all stations in 2018 ranges from 3.73 to 8.07 and the national annual mean precipitation pH value is 5.94, which is higher than those of 2010-2017. The national annual mean precipitation conductivity is 47.7 μS·cm-1 with the higher conductivity in Northern China and lower in Southern China. Compared with 2010-2017, the acid rain pollution situation over China has been improving nationwide. The precipitation chemistry data shows that the concentration of sulfate is close to nitrate in precipitation and keeps decreasing in recent years.

Applying WRF-CMAQ models for assessment of sulphur and nitrogen deposition in Bulgaria for the years 2016 and 2017

Wet, dry and total depositions of sulphur (S) and nitrogen (N) in Bulgaria are simulated on an annual and seasonal basis for the years 2016 and 2017 using WRF-CMAQ (9 km grid resolution). The mean annual values for wet depositions are about 1,300 kg.km–2, the dry depositions are slightly lower for S and significantly lower for N (180 kg.km–2). The highest modelled wet depositions are in the western and south-western parts of the country, the highest dry depositions – in the northern and eastern parts. The comparison for the wet depositions at three sites with precipitation chemistry data indicates overestimation. A precipitation bias adjustment applied to the modelled depositions results in decrease of the normalised mean bias by a factor of 3. Comparison to modelled deposition data from literature for this region of the country is also provided.

Applying WRF-CMAQ models for assessment of sulphur and nitrogen deposition in Bulgaria for the years 2016 and 2017

Wet, dry and total depositions of sulphur (S) and nitrogen (N) in Bulgaria are simulated on an annual and seasonal basis for the years 2016 and 2017 using WRF-CMAQ (9 km grid resolution). The mean annual values for wet depositions are about 1,300 kg.km–2, the dry depositions are slightly lower for S and significantly lower for N (180 kg.km–2). The highest modelled wet depositions are in the western and south-western parts of the country, the highest dry depositions – in the northern and eastern parts. The comparison for the wet depositions at three sites with precipitation chemistry data indicates overestimation. A precipitation bias adjustment applied to the modelled depositions results in decrease of the normalised mean bias by a factor of 3. Comparison to modelled deposition data from literature for this region of the country is also provided.

Sources of pollution and interrelationships between aerosol and precipitation chemistry at a central California site

This study examines co-located aerosol and precipitation chemistry data between 2010 and 2016 at Pinnacles National Monument ~65 km east of the coastline in central California. Positive matrix factorization analysis of the aerosol composition data revealed seven distinct pollutant sources: aged sea salt (25.7% of PM2.5), biomass burning (24.2% of PM2.5), fresh sea salt (15.0% of PM2.5), secondary sulfate (11.7% of PM2.5), dust (10.0% of PM2.5), vehicle emissions (8.2% of PM2.5), and secondary nitrate (5.2% of PM2.5). The influence of meteorology and transport on monthly patterns of PM2.5 composition is discussed. Only secondary sulfate exhibited a statistically significant change (a reduction) over time among the PM2.5 source factors. In contrast, PMcoarse exhibited a significant increase most likely due to dust influence. Monthly profiles of precipitation chemistry are summarized showing that the most abundant species in each month was either SO42−, NO3−, or Cl−. Intercomparisons between the precipitation and aerosol data revealed several features: (i) precipitation pH was inversely related to factors associated with more acidic aerosol constituents such as secondary sulfate and aged sea salt, in addition to being reduced by uptake of HNO3 in the liquid phase; (ii) two aerosol source factors (dust and aged sea salt) and PMcoarse exhibited a positive association with Ca2+ in precipitation, suggestive of directly emitted aerosol types with larger sizes promoting precipitation; and (iii) sulfate levels in both the aerosol and precipitation samples analyzed were significantly correlated with dust and aged sea salt PMF factors, pointing to the partitioning of secondary sulfate to dust and sea salt particles. The results of this work have implications for the region's air quality and hydrological cycle, in addition to demonstrating that the use of co-located aerosol and precipitation chemistry data can provide insights relevant to aerosol-precipitation interactions.

Preliminary evaluation of CMAQ modelled wet deposition of sulphur and nitrogen over Bulgaria

Wet depositions of sulphur and nitrogen over Bulgaria have been simulated by the WRF-CMAQ system for the period from March to June 2016. Precipitation amounts have been overestimated - the average NMB is 44% for the country and 70% for Sofia. Precipitation chemistry data from Sofia have been used for the estimation of observed sulphur and nitrogen depositions - 602 mg m−2, and 528 mg m−2, respectively. Modelled wet depositions show overestimation, more significant for sulphur deposition (NMB 87%). Precipitation adjustment has been applied as post-processing to model wet depositions. The correction led to decrease in NMB for S wet deposition (9%), while N- monthly depositions were in general underestimated. Possible effects of long-range transport for Sofia have been discussed for two selected periods of a few days.

A model validation study of the washout/rainout contribution of sulfate and nitrate in wet deposition compared with precipitation chemistry data in Japan

We simulated washout/rainout ratios of non-sea-salt (nss)-SO42− and NO3− using a chemical transport model and compared the estimates with precipitation measurements sampled at 0.5/1 mm intervals at sites located in Kobe (urban), Toyo-oka (suburban), and Tamba (rural) cities, Japan. The 25th and 75th percentile range of the simulated washout contributions was 30–70%. The simulated washout contribution range of NO3− (40–70%) was greater than that of nss-SO42− (30–60%). There was good agreement between the simulated and observed values, and the observed washout contribution of NO3− was also greater than that of SO42−. The simulated washout contribution range was higher (60–75%) in emission source regions and lower (40–55%) in downwind areas. The wet deposition process is one of the key causes of uncertainty in chemical transport modeling. Comparing model results with such high-frequency precipitation chemistry data has been extremely rare. Thus the current study is providing useful information for evaluating and improving wet deposition modeling and for the better understanding of the wet deposition mechanism.

The contribution of site to washout and rainout: Precipitation chemistry based on sample analysis from 0.5 mm precipitation increments and numerical simulation

Datasets of precipitation chemistry at a precipitation resolution of 0.5 mm from three sites were studied to determine whether the washout and rainout mechanisms differed with site type (urban, suburban, rural). Rainout accounted for approximately one-third of the total NO3− deposition and washout contributed two-thirds, irrespective of the site type, although the washout contribution at the urban site (over 70%) was larger than that at the other two sites. The rainout mechanism and the washout mechanism both accounted for about half the total SO42− deposition at the suburban and rural sites, whereas at the urban site the rainout contribution was over 80%. A chemical transport model produced similar levels of washout and rainout contributions as the precipitation chemistry data.

Chemical composition of wet precipitation at the background EMEP station in Víznar (Granada, Spain) (2002–2006)

This study describes winter precipitation chemistry data (2002–2006) from a remote regional background EMEP station located at Víznar (Granada, Spain). The rainwater samples collected were analyzed for pH, major ion concentrations and conductivity. Wet-only precipitation chemistry was dominated by Ca 2+, SO 4 2− and Cl − and the station did not have an acid rain problem (pH lies between 5.8 and 7.4). The samples were classified into nine groups of origin considering the back-trajectory and the chemical composition of the precipitation due to its meteorological origin. Saharan air masses at 1500 m and 3000 m a.g.l. seem to have an important influence on chemical rain composition. Among the marine air masses, the Mediterranean air mass carries the smallest amount of contaminants. Important correlations have been found between acidic anions (SO 4 2− and NO 3 −) and crustal-derived cations (Mg 2+, Ca 2+, and K +), suggesting the absorption of acid elements contained in aerosols, such as sulfuric acid and nitric acid, and the subsequent reaction with alkaline components rich in carbonate materials contained in particulate matter. Principal Component Factor Analysis was used in order to provide quantitative insights into the sources of specific chemical components in precipitation. Enrichment factors relative to soil and seawater have also been calculated. Although both Mg 2+ and K + have a crustal origin, a certain marine contribution is also observed.

Model Calculations of Total Maximum Daily Loads of Mercury for Drainage Lakes1

Abstract: The Watershed Analysis Risk Management Framework watershed model was enhanced to simulate the transport and fate of mercury and to calculate the fish mercury concentrations (FMC) attained by fish through the food web. The model was applied to Western Lake Superior Basin of Minnesota, which has many peat lands and lakes. Topographic, land use, and soil data were used to set up the model. Meteorology and precipitation chemistry data from nearby monitoring stations were compiled to drive the model. Simulated flow and mercury concentrations for several stream stations were comparable to available data. The model was used to perform mercury total maximum daily load calculations for two contrasting drainage lakes (Wild Rice Lake and Whiteface Reservoir). The model results for wet deposition, dry deposition, evasion, watershed yield, and soil sequestration of mercury were comparable with available actual data. The model predicted lake ice cover from November to April and weak stratification in summer, typical of shallow lakes in cold regions. The simulated sulfate decrease and methylmercury increase near the lake bottom in late summer are caused by sulfate reduction and mercury methylation that occur in the surficial sediment. Simulated FMC were within the range of observed values and the R2 of correlation between the simulated and observed FMC was 0.77. Under the 1989‐2004 base condition, the average simulated FMC of four‐year‐old walleye was 0.31 μg/g for Whiteface Reservoir and 0.15 μg/g for Wild Rice Lake. The FMC criterion in Minnesota is 0.2 μg/g. Wild Rice Lake already meets this criterion without any load reduction. The model showed that a 65% reduction in atmospheric mercury deposition will not, by itself, allow Whiteface Reservoir to meet the criterion in 15 years. Additional best management practices will be needed to reduce 50% of the watershed input.

Impacts of sulfur dioxide from Miyakejima on precipitation chemistry in Japan

Precipitation chemistry data of Japanese Acid Deposition Survey (JADS) by Japan Ministry of the Environment was analyzed to evaluate the influence of SO 2 emitted from the volcano of Miyakejima located in the Pacific Ocean 200 km south of Tokyo. Precipitation samples were collected with wet-only samplers on a daily basis at eight sites over Japan. The sampling periods (1997–2005) were divided into three periods in consideration of the start of the eruption, August 2000: 1997–1999 (Period A), 2000–2002 (Period B), 2003–2005 (Period C). The influence was evaluated in terms of the ratio before-to-after the eruption, B/A and C/A. The B/A ratios for mean nss-SO 4 2− concentration ranged from 1.1 to 2.3. The average pH decreased at most sites in Period B. The ratios for annual deposition were the same level as those of the concentration. The influence was also assessed for daily concentration and deposition at Tanzawa and Tsukuba, the two closest sites to Miyakejima. The cumulative frequency distributions of the daily nss-SO 4 2− concentration shifted to higher concentration for both sites in Period B. Daily pH cumulative frequency distributions shifted to lower values at both sites in Period B. The monthly fraction, nss-SO 4 2−/(nss-SO 4 2− + NO 3 −), increased immediately after the eruption onset. The eruption was found to have influenced concentrations and deposition of nss-SO 4 2− and pH on a national scale, and the sites closest to Miyakejima showed the largest influence.

Role of aerosols in deciding pH of rainwater

Nature of precipitation – alkaline or acidic – depends upon the concentration of major water soluble inorganic gaseous and soil derived particulates dissolved in it. If concentration of cations is higher than that of anions, the precipitation becomes alkaline and vise-a-versa.
 pH is the main parameter indicating the nature of precipitation. If pH of the solution is < 5.65, it is acidic and > 5.65, alkaline, in the pH scale ranging between 0 & 14.
 Difference in the chemical composition of rainwater having pH in the alkaline range and acidic range has been studied in this paper. For this purpose, precipitation chemistry data of Allahabad, Jodhpur, Mohanbari and Nagpur for the period 1988-97 have been considered. APWM & S.D. have been worked out. Precipitation chemistry data considering APWM values in acidic range and in alkaline range have been separated and compared. Coefficients of correlation have been calculated in possible cation-anion combinations.
 It is seen that the lowest pH values (monthly mean) have been recorded during 1997 – MHB (3.77), NGP (4.12), both in acidic range. % Frequency of occurrences of pH values in acidic range was the highest at Mohanbari (66%) in the study period. Jodhpur recorded all pH values in alkaline range indicating influence of soil derived alkaline particulates. Among cations Ca+² has shown its dominance over all cations. Jodhpur has recorded the highest APWM value of Ca+² (9.27mg/lit) in 1997.
 Data have also been compared with WMO Laboratory simulated acid rain sample analysis data and other non-departmental data.
 Results are discussed in the paper.

Trends of bulk precipitation and Streamwater Chemistry in a Small Mountainous Watershed on the Shikoku Island of Japan

For this study, characteristics and trends of the chemical constituents in bulk precipitation and streamwater were observed in a small mountainous watershed on the Shikoku Island of Japan, which covered an area of 27.4 hectares. Bulk precipitation and streamwater chemistry data spans from May 1997 to October 2004, and January 1996 to October 2004, respectively. The data were tested for two types of trends: (1) a monotonic trend to determine if concentrations of the chemical constituents were generally decreasing, increasing, or stable during the study period, and (2) a step trend to determine if a change occurred following the December 1999-January 2000 forest thinning. Both parametric and non-parametric statistical analyses were carried out in this study. Although the study area is only 35 km away from the Pacific Ocean, bulk precipitation chemistry was also influenced by terrestrial sources to a large extent. Streamwater chemistry was influenced by bedrock weathering, which was dominated by Ca2+ and HCO3−, and was not strongly related top recipitation chemistry.Non−parametric Seasonal Kendall Test(SKT)showedadeceasingtr end of Ca2+and anincreasing tr end of K+in bulk precipitation.Despite the decreasing trend of Mg2+, an increasing trend of pH was found in the stream water.Non−paramet ric Mann−Whit ney−Wilcoxon Rank Sum test showed statistically sign if icantin creases of NO3−and Ca2+ in stream water followed by a moderate thinning operation.

Seasonal NH 3 emissions for the continental united states: Inverse model estimation and evaluation

Significant uncertainty exists in the seasonal distribution of NH 3 emissions since the predominant sources are animal husbandry and fertilizer application. Previous studies that estimated bottom–up and top–down NH 3 emissions have provided the most comprehensive information available about the seasonality of NH 3 emissions. In this study, this bottom–up and top–down emission information is combined with the most recent 2001 USEPA National Emission Inventory (NEI) to construct a best prior estimate of seasonal NH 3 emissions. These emission estimates are then used in an annual 2001 USEPA Community Multiscale Air Quality (CMAQ) model simulation for the continental United States. A key objective of this study is to evaluate these prior NH 3 emission estimates and test the top–down inverse modeling method for a different year and a larger modeling domain than used previously. Based on the final posterior NH 3 emission estimates, the inverse modeling results suggest that the annual total NEI NH 3 emissions are reasonable and that a previous high bias in older USEPA emission inventories has been addressed in the updated inventory. Inverse modeling results suggest that the prior NH 3 emission estimates should be increased in the summer and decreased in the winter, while results for the spring and fall are questionable due to precipitation prediction biases. A final conclusion from this study is that total NH x (NH 3 and aerosol NH 4 +) air concentration data are essential for quantitative top–down analyses of NH 3 emissions that can extend beyond what is possible using precipitation chemistry data.

Application of Bayesian Regularized BP Neural Network Model for Trend Analysis, Acidity and Chemical Composition of Precipitation in North Carolina

Bayesian regularized back-propagation neural network (BRBPNN) was developed for trend analysis, acidity and chemical composition of precipitation in North Carolina using precipitation chemistry data in NADP. This study included two BRBPNN application problems: (i) the relationship between precipitation acidity (pH) and other ions (NH4 +, NO3 −, SO4 2−, Ca2+, Mg2+, K+, Cl− and Na+) was performed by BRBPNN and the achieved optimal network structure was 8-15-1. Then the relative importance index, obtained through the sum of square weights between each input neuron and the hidden layer of BRBPNN(8-15-1), indicated that the ions' contribution to the acidity declined in the order of NH4 + > SO4 2− > NO3 −; and (ii) investigations were also carried out using BRBPNN with respect to temporal variation of monthly mean NH4 +, SO4 2− and NO3 − concentrations and their optimal architectures for the 1990–2003 data were 4-6-1, 4-6-1 and 4-4-1, respectively. All the estimated results of the optimal BRBPNNs showed that the relationship between the acidity and other ions or that between NH4 +, SO4 2−, NO3 − concentrations with regard to precipitation amount and time variable was obviously nonlinear, since in contrast to multiple linear regression (MLR), BRBPNN was clearly better with less error in prediction and of higher correlation coefficients. Meanwhile, results also exhibited that BRBPNN was of automated regularization parameter selection capability and may ensure the excellent fitting and robustness. Thus, this study laid the foundation for the application of BRBPNN in the analysis of acid precipitation.

Response of surface water chemistry to reduced levels of acid precipitation: comparison of trends in two regions of New York, USA

AbstractIn light of recent reductions in sulphur (S) and nitrogen (N) emissions mandated by Title IV of the Clean Air Act Amendments of 1990, temporal trends and trend coherence in precipitation (1984–2001 and 1992–2001) and surface water chemistry (1992–2001) were determined in two of the most acid‐sensitive regions of North America, i.e. the Catskill and Adirondack Mountains of New York. Precipitation chemistry data from six sites located near these regions showed decreasing sulphate (SO42−), nitrate (NO3−), and base cation (CB) concentrations and increasing pH during 1984–2001, but few significant trends during 1992–2001. Data from five Catskill streams and 12 Adirondack lakes showed decreasing trends in SO42− concentrations at all sites, and decreasing trends in NO3−, CB, and H+ concentrations and increasing trends in dissolved organic carbon at most sites. In contrast, acid‐neutralizing capacity (ANC) increased significantly at only about half the Adirondack lakes and in one of the Catskill streams. Flow correction prior to trend analysis did not change any trend directions and had little effect on SO42− trends, but it caused several significant non‐flow‐corrected trends in NO3− and ANC to become non‐significant, suggesting that trend results for flow‐sensitive constituents are affected by flow‐related climate variation. SO42− concentrations showed high temporal coherence in precipitation, surface waters, and in precipitation–surface water comparisons, reflecting a strong link between S emissions, precipitation SO42− concentrations, and the processes that affect S cycling within these regions. NO3− and H+ concentrations and ANC generally showed weak coherence, especially in surface waters and in precipitation–surface water comparisons, indicating that variation in local‐scale processes driven by factors such as climate are affecting trends in acid–base chemistry in these two regions. Copyright © 2005 John Wiley & Sons, Ltd.

Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8 km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8 km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.