Aspects of uncertainty in total reactive nitrogen deposition estimates for North American critical load applications

River Basin Export Reduction Optimization Support Tool; a tool to screen options for reducing nutrient loads while minimizing cost

Excess loading of nitrogen and phosphorus to river networks causes environmental harm, but reducing loads from large river basins is difficult and expensive. We develop a new tool, the River Basin Export Reduction Optimization Support Tool (RBEROST) to identify least-cost combinations of management practices that will reduce nutrient loading to target levels in downstream and mid-network waterbodies. We demonstrate the utility of the tool in a case study in the Upper Connecticut River basin in New England, USA. The total project cost of optimized lowest-cost plans ranged from $18.0 million to $41.0 million per year over 15 years depending on user specifications. Plans include both point source and non-point source management practices, and most costs are associated with urban stormwater practices. Adding a 2% margin of safety to loading targets improved estimated probability of success from 37.5% to 99%. The large spatial scale of RBEROST, and the consideration of both point and non-point source contributions of nutrients, makes it well suited as an initial screening tool in watershed planning.

Empirical nitrogen and sulfur critical loads of U.S. tree species and their uncertainties with machine learning

Critical loads (CLs) of atmospheric deposition for nitrogen (N) and sulfur (S) are used to support decision making related to air regulation and land management. Frequently, CLs are calculated using empirical methods, and the certainty of the results depends on accurate representation of underlying ecological processes. Machine learning (ML) models perform well in empirical modeling of processes with non-linear characteristics and significant variable interactions. We used bootstrap ensemble ML methods to develop CL estimates and assess uncertainties of CLs for the growth and survival of 108 tree species in the conterminous United States. We trained ML models to predict tree growth and survival and characterize the relationship between deposition and tree species response. Using four statistical methods, we quantified the uncertainty of CLs in 95 % confidence intervals (CI). At the lower bound of the CL uncertainty estimate, 80 % or more of tree species have been impacted by nitrogen deposition exceeding a CL for tree survival over >50 % of the species range, while at the upper bound the percentage is much lower (<20 % of tree species impacted across >60 % of the species range). Our analysis shows that bootstrap ensemble ML can be effectively used to quantify critical loads and their uncertainties. The range of the uncertainty we calculated is sufficiently large to warrant consideration in management and regulatory decision making with respect to atmospheric deposition.

Modeled Vegetation Community Trajectories: Effects from Climate Change, Atmospheric Nitrogen Deposition, and Soil Acidification Recovery

Forest understory plant communities in the United States harbor most of the vegetation diversity of forests and are often sensitive to changes in climate and atmospheric deposition of nitrogen (N). As temperature increases from human-caused climate change and soils recover from long term atmospheric deposition of N and sulfur (S), it is unclear how these important ecosystem components will respond. We used the newly developed US-PROPS model - based on species response functions for over 1,500 species - to evaluate the potential impacts of atmospheric N deposition and climate change on species occurrence probability for a case study in the forested ecosystems of the Great Smoky Mountains National Park (GRSM), an iconic park in the southeastern United States. We evaluated six future scenarios from various combinations of two potential recoveries of soil pH (no change, +0.5 pH units) and three climate futures (no change, +1.5, +3.0 deg C). Species critical loads (CLs) of N deposition and projected responses for each scenario were determined. Critical loads were estimated to be low (< 2 kg N/ha/yr) to protect all species under current and expected future conditions across broad regions of GRSM and these CLs were exceeded at large spatial extents among scenarios. Northern hardwood, yellow pine, and chestnut oak forests were among the most N-sensitive vegetation map classes found within GRSM. Potential future air temperature conditions generally led to decreases in the maximum occurrence probability for species. Therefore, CLs were considered "unattainable" in these situations because the specified level of protection used for CL determination (i.e., maximum occurrence probability under ambient conditions) was not attainable. Although some species showed decreases in maximum occurrence probability with simulated increases in soil pH, most species were favored by increased pH. The importance of our study is rooted in the methodology described here for establishing regional CLs and for evaluating future conditions, which is transferable to other national parks in the U.S. and in Europe where the original PROPS model was developed.

Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales

Increased nitrogen (N) deposition rates over the past century have affected both North American and European mountain lake ecosystems. Ecological sensitivity of mountain lakes to N deposition varies, however, because chemical and biological responses are modulated by local watershed and lake properties. We evaluated predictors of mountain lake sensitivity to atmospheric N deposition across North American and European mountain ranges and included as response variables dissolved inorganic N (DIN = NNH4+ + NNO3-) concentrations and phytoplankton biomass. Predictors of these responses were evaluated at three different spatial scales (hemispheric, regional, subregional) using regression tree, random forest, and generalized additive model (GAM) analysis. Analyses agreed that Northern Hemisphere mountain lake DIN was related to N deposition rates and smaller scale spatial variability (e.g., regional variability between North American and European lakes, and subregional variability between mountain ranges). Analyses suggested that DIN, N deposition, and subregional variability were important for Northern Hemisphere mountain lake phytoplankton biomass. Together, these findings highlight the need for finer-scale, subregional analyses (by mountain range) of lake sensitivity to N deposition. Subregional analyses revealed differences in predictor variables of lake sensitivity. In addition to N deposition rates, lake and watershed features such as land cover, bedrock geology, maximum lake depth (Zmax), and elevation were common modulators of lake DIN. Subregional phytoplankton biomass was consistently positively related with total phosphorus (TP) in Europe, while North American locations showed variable relationships with N or P. This study reveals scale-dependent watershed and lake characteristics modulate mountain lake ecological responses to atmospheric N deposition and provides important context to inform empirically based management strategies.

Satellite-Based Estimates of Wet Ammonium (NH4-N) Deposition Fluxes Across China during 2011-2016 Using a Space-Time Ensemble Model

Wet NH₄-N deposition plays a significant role in the ecosystem safety in China, and thus it is highly imperative to estimate the national wet NH₄-N deposition flux accurately. In this study, a new methodology named space-time ensemble machine-learning model was first applied to constrain the high-resolution NH₄-N deposition fluxes over China based on the satellite data, assimilated meteorology, and various geographical covariates. A small gap between site-based cross-validation (CV) R² value (0. 73) and 10-fold CV R² value (0.76), along with remarkable improvement in predictive accuracy (0.76) compared with previous studies (0.61), demonstrated the strong prediction capability of the space-time ensemble model in data mining. The higher wet NH₄-N deposition fluxes mainly occurred in North China Plain (NCP), Sichuan Basin, Hunan, Jiangxi, and Guangdong provinces, whereas other regions retained the lower values. In addition, the wet NH₄-N deposition fluxes, removing the precipitation effect in some major developed regions (e.g., Beijing and Shanghai) of China, displayed gradual increases from 2011 to 2014, while they suffered from dramatic decreases during 2014-2016, which was due to the strict implementation of the Action Plan for Air Pollution Prevention and Control (APPC-AP). The high-quality NH₄-N deposition data sets are greatly useful to assess the potential ecological risks.

Dry deposition of reactive nitrogen to different ecosystems across eastern China: A comparison of three community models

The assessment of nitrogen ecosystem loads mostly use the method of sampling observation combined with numerical model to estimate the spatial distribution pattern of nitrogen dry deposition flux. The selection of models is important which directly affects the reliability of the deposition flux results. In this study, the performance of three widely used models (WRF-Chem, EMEP, CMAQ) are compared. The dry deposition fluxes of typical active nitrogen components over eastern China showed uncertainties by a factor of 0.5 ~ 2 between the oxidized nitrogen (OXN) results of the three models and the observation network while the reduced nitrogen (RDN) simulation results are underestimated by a quarter of the observation reports. These three models show different results on four typical ecosystems: simulation of EMEP got the highest for OXN dry deposition flux on each ecosystem (urban 14.94 ± 4.92kgN ⋅ ha^-1 ⋅ yr^-1, cropland/grassland 5.53 ± 5.11kgN ⋅ ha^-1 ⋅ yr^-1, forest 4.75 ± 4.32kgN ⋅ ha^-1 ⋅ yr^-1, water bodies 1.48 ± 1.53kgN ⋅ ha^-1 ⋅ yr^-1); WRF-Chem has the highest value of RDN on the urban (8.91 ± 6.44kgN ⋅ ha^-1 ⋅ yr^-1) and water bodies (1.01 ± 1.44kgN ⋅ ha^-1 ⋅ yr^-1) while EMEP is highest in cropland/grassland (3.42 ± 3.43kgN ⋅ ha^-1 ⋅ yr^-1) and forest (2.34 ± 1.94kgN ⋅ ha^-1 ⋅ yr^-1). CMAQ is in medium range for both OXN and RDN simulations on each ecosystem. Compare with the critical loads, CMAQ generates more exceeded critical load areas than WRF-Chem and EMEP on cropland/grassland and forests ecosystem. For water bodies, WRF-chem and CMAQ showed higher exceeding critical load areas than EMEP. In summary, EMEP generally underestimates while the CMAQ and WRF-Chem model would overestimate the impacts on the ecosystems. So, policy implementation needs special attention accounting the difference of simulation effect with different models.

Source, contribution and microbial N-cycle of N-compounds in China fresh snow

The importance and contribution of nitrogen compounds and the related microbial nitrogen cycling processes in fresh snow are not well understood under the current research background. We collected fresh snow samples from 21 cities that 80% are from China during 2016 and 2017. Principal component analysis showed that SO₄^2- were in the first principal component, and N-compounds were the second. Furthermore, the main pollutant ions SO₄^2- and NO₃^- were from anthropogenic sources, and SO₄^2- contributed (61%) more to the pollution load than NO₃^- (29%), which were confirmed through a series of precipitation mechanism analysis. We selected five N-cycle processes (consist of oxidation and reduction processes) for molecular biology experiments, including Ammonia-oxidation process, Nitrite-oxidation process, Denitrification process, Anaerobic-ammoxidation process (Anammox) and Dissimilatory nitrate reduction to ammonium process (DNRA). Except ammonia-oxidizing archaeal (AOA) and bacterial (AOB) amoA genes (above 10⁷ copies g^-1), molecular assays of key functional genes in various nitrogen conversion processes showed a belowed detection limit number, and AOB abundance was always higher than AOA. The determination of the microbial transformation rate using the ¹⁵N-isotope tracer technique showed that the potential rate of five N-conversion processes was very low, which is basically consistent with the results from molecular biology studies. Taken together, our results illustrated that microbial nitrogen cycle processes are not the primary biological processes causing the pollution in China fresh snow.

A review of measurements of air-surface exchange of reactive nitrogen in natural ecosystems across North America

This review summarizes the state of the science of measurements of dry deposition of reactive nitrogen (Nr) compounds in North America, beginning with current understanding of the importance of dry deposition at the U.S. continental scale followed by a review of micrometeorological flux measurement methods. Measurements of Nr air-surface exchange in natural ecosystems of North America are then summarized, focusing on the U.S. and Canada. Drawing on this synthesis, research needed to address the incompleteness of dry deposition budgets, more fully characterize temporal and geographical variability of fluxes, and better understand air-surface exchange processes is identified. Our assessment points to several data and knowledge gaps that must be addressed to advance dry deposition budgets and air-surface exchange modeling for North American ecosystems. For example, recent studies of particulate (NO3-) and gaseous (NOx, HONO, peroxy nitrates) oxidized N fluxes challenge the fundamental framework of unidirectional flux from the atmosphere to the surface employed in most deposition models. Measurements in forest ecosystems document the importance of in-canopy chemical processes in regulating the net flux between the atmosphere and biosphere, which can result in net loss from the canopy. These results emphasize the need for studies to quantify within- and near-canopy sources and sinks of the full suite of components of the Nr chemical system under study (e.g., NOy or HNO3-NH3-NH4NO3). With respect to specific ecosystems and geographical locations, additional flux measurements are needed particularly in agricultural regions (NH3), coastal zones (NO3- and organic N), and arid ecosystems and along urban to rural gradients (NO2). Measurements that investigate non-stomatal exchange processes (e.g., deposition to wet surfaces) and the biogeochemical drivers of bidirectional exchange (e.g., NH3) are considered high priority. Establishment of long-term sites for process level measurements of reactive chemical fluxes should be viewed as a high priority long-term endeavor of the atmospheric chemistry and ecological communities.

Toward the improvement of total nitrogen deposition budgets in the United States

Frameworks for limiting ecosystem exposure to excess nutrients and acidity require accurate and complete deposition budgets of reactive nitrogen (Nr). While much progress has been made in developing total Nr deposition budgets for the U.S., current budgets remain limited by key data and knowledge gaps. Analysis of National Atmospheric Deposition Program Total Deposition (NADP/TDep) data illustrates several aspects of current Nr deposition that motivate additional research. Averaged across the continental U.S., dry deposition contributes slightly more (55%) to total deposition than wet deposition and is the dominant process (>90%) over broad areas of the Southwest and other arid regions of the West. Lack of dry deposition measurements imposes a reliance on models, resulting in a much higher degree of uncertainty relative to wet deposition which is routinely measured. As nitrogen oxide (NOx) emissions continue to decline, reduced forms of inorganic nitrogen (NHx = NH3 + NH4+) now contribute >50% of total Nr deposition over large areas of the U.S. Expanded monitoring and additional process-level research are needed to better understand NHx deposition, its contribution to total Nr deposition budgets, and the processes by which reduced N deposits to ecosystems. Urban and suburban areas are hotspots where routine monitoring of oxidized and reduced Nr deposition is needed. Finally, deposition budgets have incomplete information about the speciation of atmospheric nitrogen; monitoring networks do not capture important forms of Nr such as organic nitrogen. Building on these themes, we detail the state of the science of Nr deposition budgets in the U.S. and highlight research priorities to improve deposition budgets in terms of monitoring and flux measurements, leaf- to regional-scale modeling, source apportionment, and characterization of deposition trends and patterns.

Assessing Ecological Risks from Atmospheric Deposition of Nitrogen and Sulfur to US Forests Using Epiphytic Macrolichens

Critical loads of atmospheric deposition help decision-makers identify levels of air pollution harmful to ecosystem components. But when critical loads are exceeded, how can the accompanying ecological risk be quantified? We use a 90% quantile regression to model relationships between nitrogen and sulfur deposition and epiphytic macrolichens, focusing on responses of concern to managers of US forests: Species richness and abundance and diversity of functional groups with integral ecological roles. Analyses utilized national-scale lichen survey data, sensitivity ratings, and modeled deposition and climate data. We propose 20, 50, and 80% declines in these responses as cut-offs for low, moderate, and high ecological risk from deposition. Critical loads (low risk cut-off) for total species richness, sensitive species richness, forage lichen abundance and cyanolichen abundance, respectively, were 3.5, 3.1, 1.9, and 1.3 kg N and 6.0, 2.5, 2.6, and 2.3 kg S ha⁻¹ yr⁻¹. High environmental risk (80% decline), excluding total species richness, occurred at 14.8, 10.4, and 6.6 kg N and 14.1, 13, and 11 kg S ha⁻¹ yr⁻¹. These risks were further characterized in relation to geography, species of conservation concern, number of species affected, recovery timeframes, climate, and effects on interdependent biota, nutrient cycling, and ecosystem services.