Atmospheric Ammonia Concentrations Research Articles

Study on the formation and ignition law of ignition core in ammonia atmosphere diesel cylinder

Ammonia fuel does not contain carbon and is a kind of very good zero-carbon alternative fuel for diesel engines. However, ammonia is difficult to be ignited in diesel engine. The dual-fuel combustion mode of ammonia and diesel is an effective technical means to solve the problem. In this paper, the 186FA diesel engine test bench was built, and the ammonia/diesel dual fuel combustion mode was formed by injecting 0 %, 10 %, 20 %, 30 %, 40 %, and 50 % ammonia into the inlet and direct injection of diesel into the cylinder. The in-cylinder pressure and heat release laws were measured and analyzed at 2700r/min, 25 % load and 75 % load. Based on the analysis of the oxidation in ignition process of ammonia gas and diesel, a computational fluid dynamics model of the ignition process was established. By comparing the temperature contour surface in the cylinder and the concentration contour surface of OH radical, the paper put forward the ignition core evaluation index suitable for diesel/ammonia dual fuel. The formation law of the ignition core of diesel injected in homogeneous low reactive ammonia atmosphere in the cylinder was analyzed, and the influence of ammonia on the ignition process of diesel was revealed. The results show that the ignition delay period is prolonged after adding ammonia, and there is an exponential function relationship between the ignition delay period and the atmospheric concentration of ammonia. At 1200 K, there is an obvious parabolic relationship between ammonia concentration and OH radical concentration. The ignition core area was increased with the increase of ammonia concentration. Compared with pure diesel mode, the single ignition core at 75 % load of 2700 r/min is 3.6 times larger at 50 % ammonia atmosphere concentration. The ignition core will move up the diesel bundle with the increase of ammonia concentration. The study of chemical reaction kinetics showed that the reaction NH3 + OH = NH2 + H2O displayed positive sensitivity when ammonia concentration was less than 10 % and negative sensitivity when ammonia concentration was more than 10 %. The difference in sensitivity is the reason why the phase of the maximum burst pressure in the 10 % ammonia atmosphere is slightly earlier.

Application of Machine Learning to Estimate Ammonia Atmospheric Emissions and Concentrations

This paper describes an innovative method that recursively applies the machine learning Random Forest to an assumed homogeneous aerographic domain around measurement sites to predict concentrations and emissions of ammonia, an atmospheric pollutant that causes acidification and eutrophication of soil and water and contributes to secondary PM2.5. The methodology was implemented to understand the effects of weather and emission changes on atmospheric ammonia concentrations. The model was trained and tested by hourly measurements of ammonia concentrations and atmospheric turbulence parameters, starting from a constant emission scenario. The initial values of emissions were calculated based on a bottom-up emission inventory detailed at the municipal level and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations for each iteration, the emissions were modified, the model’s training and testing were repeated, and the model converged to a very high performance in predicting ammonia concentrations and establishing hourly time-varying emission profiles. The ammonia concentration predictions were extremely accurate and reliable compared to the measured values. The relationship between NH3 concentrations and the calculated emissions rates is compatible with physical atmospheric turbulence parameters. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow the identification of the effect of atmospheric turbulence on pollutant accumulation. The proposed methodology is suitable for validating and confirming emission time series and defining highly accurate emission profiles for the improvement of the performances of chemical and transport models (CTMs) in combination with in situ measurements and/or optical depth from satellite observation.

Revisiting the dynamics of gaseous ammonia and ammonium aerosols during the COVID-19 lockdown in urban Beijing using machine learning models

The concentration of atmospheric ammonia (NH3) in urban Beijing substantially decreased during the COVID-19 lockdown (24 January to 3 March 2020), likely due to the reduced human activities. However, quantifying the impact of anthropogenic interventions on NH3 dynamics is challenging, as both meteorology and chemistry mask the real changes in observed NH3 concentrations. Here, we applied machine learning techniques based on random forest models to decouple the impacts of meteorology and emission changes on the gaseous NH3 and ammonium aerosol (NH4+) concentrations in Beijing during the lockdown. Our results showed that the meteorological conditions were unfavorable during the lockdown and tended to cause an increase of 8.4 % in the NH3 concentration. In addition, significant reductions in NOx and SO2 emissions could also elevate NH3 concentrations by favoring NH3 gas-phase partitioning. However, the observed NH3 concentration significantly decreased by 35.9 % during the lockdown, indicating a significant reduction in emissions or enhanced chemical sinks. Rapid gas-to-particle conversion was indeed found during the lockdown. Thus, the observed reduced NH3 concentrations could be partially explained by the enhanced transformation into NH4+. Therefore, the sum of NH3 and NH4+ (collectively, NHx) is a more reliable tracer than NH3 or NH4+ alone to estimate the changes in NH3 emissions. Compared to that under the scenario without lockdowns, the NHx concentration decreased by 26.4 %. We considered that this decrease represents the real decrease in NH3 emissions in Beijing due to the lockdown measures, which was less of a decrease than that based on NH3 only (35.9 %). This study highlights the importance of considering chemical sinks in the atmosphere when applying machine learning techniques to link the concentrations of reactive species with their emissions.

Concurrent measurements of atmospheric ammonia concentrations in the megacities of Beijing and Shanghai by using cavity ring-down spectroscopy

Ammonia (NH3) is a vital precursor of secondary aerosols, which play an important role in urban air pollution. The passive observation of NH3 in the urban atmosphere showed higher concentrations than conventionally believed; however, the NH3 dynamics remain limited due to the paucity of active measurements with fast response instruments. In this study, intensive online measurements of ambient NH3 were conducted using cavity ring-down spectroscopy in late spring and early summer 2020 at the megacities of Beijing and Shanghai in northern and southern China. The results show that the average NH3 concentration in Beijing (23.1 ± 10.3 ppb) was nearly double that in Shanghai (12.0 ± 5.0 ppb). This spatial difference was confirmed by satellite column observations and bottom-up emission patterns. In addition, there was a significant increase in NH3 concentrations during the morning in our study. This special diurnal profile was a universal feature, with an occurrence frequency exceeding 50% in both cities. These frequent morning increases were mainly caused by motor vehicle emissions, with an additional contribution from the residual layer breakup for one-quarter of the days in the morning increase. On these days, the NH3 concentration increased by approximately 20% due to the downward mixing of the residual layer rupture. The unique data observed here could be used to validate the chemistry and transport models at a higher time resolution and improve the understanding of the current status of NH3 pollution in the urban atmosphere.

Atmospheric ammonia in China: Long-term spatiotemporal variation, urban-rural gradient, and influencing factors

In recent years, atmospheric ammonia (NH3) concentrations have increased in China. Ammonia control has become one of the next hot topics in air pollution mitigation with the increasing cost of acid gas emission reduction. In this study, using Infrared Atmospheric Sounding Interferometer (IASI) satellite observations, we analyzed the spatiotemporal distribution, the urban-rural gradient of the vertical column densities (VCDs) of NH3 and the contribution of influencing factors (meteorology, social, atmospheric acid gases, and NH3 emissions) in China from 2008 to 2019 using hotspot analysis, circular gradient analysis, geographical and temporal weighted regression, and some other methods. Our results showed that NH3 VCDs in China have significantly increased (31.88 %) from 2008 to 2019, with the highest occurring in North China Plain. The average NH3 VCDs in urban areas were significantly higher than those in rural areas, and the urban-rural gap in NH3 VCDs was widening. The results of circular gradient analysis showed an overall decreasing trend in NH3 VCDs along the urban-rural gradient. We used a geographically and temporally weighted regression model to analyze the contribution of various influencing factors to NH3 VCDs: meteorology (30.13 %), social (27.40 %), atmospheric acid gases (23.20 %), and NH3 emissions (19.28 %) factors. The results showed substantial spatiotemporal differences in the influencing factors. Atmospheric acid gas was the main reason for the increase in NH3 VCDs from 2008 to 2019. A more thorough understanding of the spatiotemporal distribution, urban-rural variations, and factors influencing NH3 in China will aid in developing control strategies to reduce PM2.5.

Impact of COVID-19 restrictions on the concentration and source apportionment of atmospheric ammonia (NH3) across India

The wide spread of the coronavirus disease (COVID-19) has significantly influenced human activities around the world, providing a unique opportunity to investigate the response of air pollution to anthropogenic emission reduction. Compared with numerous studies on conventional air pollutants, atmospheric ammonia (NH3) that has matched sources from both anthropogenic and natural emissions has been rarely investigated. Here we assess impacts of the COVID-19 lockdown on ambient NH3 variation across India, one of the most severe NH3 pollution region in the world. The role of meteorology in shaping emission contribution to NH3 pollution and respective contribution of each emission source to ambient NH3 before and after the COVID-19 outbreak were investigated using the XGBoost algorithm coupled with WRF-Chem model. Results showed that ambient NH3 concentrations in the seven major cities (Hyderabad, Bengaluru, Chennai, Delhi, Lucknow, Kolkata and Mumbai) decreased by 2.1–53.8 % whereas in Ahmedabad increased by 20.3 % during the COVID-19 lockdown period. Obvious decrease in NH3 in Indo-Gangetic Plain (−17.1 %) was mainly driven by favorable meteorology, whereas the slight decline in NH3 in South India was mainly driven by epidemic-related emission control (−8.56 %). Source appointment results showed that the contribution of industrial emission (Ind) to ambient NH3 in most megacities showed a decreasing trend (between 11 % and 26 %) during the lockdown period. However, the reduction effect was mostly compensated by increasing contributions (15–25 %) of residential emission (Res) or agricultural soil emission (Ags). Particularly, in Ahmedabad and Lucknow ambient NH3 increased by 20.3 % and 12 % during the lockdown period, the reduction effect of Ind on ambient NH3 (−23 % and −11 %, respectively) was absolutely compensated by enhanced contribution of Res (24 %) and Ags (12 %), respectively. Our results highlight the importance of eliminating residential and agricultural NH3 emissions especially in North India.

Effects of elevated atmospheric ammonia concentration on photosynthetic characteristics and grain yield in wheat under different nitrogen rates.

To evaluate the effects of nitrogen (N) application rates on the growth, photosynthetic traits and yield of winter wheat under elevated atmospheric ammonia (NH3) concentrations could provide guidance for N management under high NH3 environment. We conducted a split-plot experiment for two consecutive years (2020-2021 and 2021-2022) with top-open chambers. The treatments included two NH3 concentrations [elevated ambient NH3 concentration at 0.30-0.60 mg·m-3 (EAM) and air NH3 concentration at 0.01-0.03 mg·m-3 (AM)] and two N application rates [recommended N dose (+N) and no N application (-N)]. We analyzed the effects of aforementioned treatments on net photosynthetic rate (Pn), stomatal conductance (gs), chlorophyll content (SPAD value), plant height, and grain yield. The results showed that averaged across the two years, EAM significantly increased Pn, gs, and SPAD values at the jointing and booting stages at the -N level by 24.6%, 16.3%, 21.9% and 20.9%, 37.1%, 5.7%, respectively, compared with AM. However, EAM significantly decreased Pn, gs, and SPAD values at jointing and booting stages at +N level by 10.8%, 5.9%, 3.6% and 6.8%, 18.9%, 9.3%, respectively, over AM treatment. There was a significant effect of NH3 treatment, N application rates and their interaction on plant height and grain yield. Compared with AM, EAM increased the average plant height and grain yield by 4.5% and 32.1% at -N level and decreased by 1.1% and 8.5% at +N level, respectively. In a nutshell, the eleva-ted ambient NH3 concentration had positive effect on photosynthetic characteristics, plant height, and grain yield under ambient N condition, but a inhibitory effect under N application.

NH3 concentrations below the current critical level affect the epiphytic macrolichen communities – Evidence from a Northern European City

Acidophytic, oligotrophic lichens on tree trunks are widely considered to be the most sensitive biota to elevated concentrations of atmospheric ammonia (NH3). We studied the relationships between measured NH3 concentrations and the composition of macrolichen communities on the acidic bark of Pinus sylvestris and Quercus robur and the base-rich bark of Acer platanoides and Ulmus glabra at ten roadside and ten non-roadside sites in Helsinki, Finland. NH3 and nitrogen dioxide (NO2) concentrations were higher at the roadside than non-roadside sites indicating traffic as the main source of NH3 and nitrogen oxides (NOx). The diversity of oligotrophs on Quercus was lower at the roadside than non-roadside sites, while that of eutrophs was higher. The abundance and presence of oligotrophic acidophytes (e.g., Hypogymnia physodes) decreased with increasing NH3 concentration (2-year means = 0.15–1.03 μg m−3) especially on Q. robur, while those of eutrophic/nitrophilous species (e.g., Melanohalea exasperatula, Physcia tenella) increased. The abundance of some nitrophytes seemed to depend only on bark pH, i.e., their abundances were highest on Ulmus, which had the highest average bark pH. Overall, the results of lichen bioindicator studies may depend on tree species (bark pH) and lichen species used in calculating indices describing the air quality impact. Nevertheless, Quercus is recommended to be used to study the impact of NH3 alone and in combination with NOx on lichen communities, because the responses of both oligotrophic acidophytes and eutrophic species can already be observed at NH3 concentrations below the current critical level.

Increasing the accuracy of atmospheric ammonia concentrations calculated from Open-Path Fourier transform infrared spectra using partial least squares model by scanning and removing interference spectral data

Monitoring atmospheric pollutants has raised worldwide concerns in last decades, due to deterioration of air quality. Multivariate regression methods have gained extensive applications in calculating and monitoring concentrations of air pollutants, for example ammonia (NH 3 ), using Open-Path Fourier Transform Infrared (OP/FT-IR) spectra data. However, the prediction accuracy of multivariate regression models is interfered heavily by the dominant and omnipresent absorption bands of atmospheric H 2 O vapor and CO 2 in OP/FT-IR spectra. Hence, a new method of variable selection, referred to as window of scanning and removing interference information (WSRII), is developed to remove interference data of OP/FT-IR spectra. The key of WSRII is to confirm informative variables according to the change of root mean square error of calibration in the partial least squares regression (PLSR) model after removing a spectral window. If the change is greater than 0, the spectral window is reserved as an informative information window. Then, the new matrixes of spectral data are reconstructed by using the informative information windows, which are selected by changing position of the spectral window in full wave number range. Based on this, a PLSR model is rebuilt to predict accurately NH 3 concentrations. The results showed that the proposed method was able to eliminate uninformative information and improved prediction accuracy of PLSR models. Moreover, this process of variable selection is significantly potential to improve prediction accuracy of PLSR model for monitoring atmospheric NH 3 concentrations in real time.

Secondary PM<sub>2.5</sub> decreases significantly less than NO<sub>2</sub> emission reductions during COVID lockdown in Germany

Abstract. This study estimates the influence of anthropogenic emission reductions on the concentration of particulate matter with a diameter smaller than 2.5 µm (PM2.5) during the 2020 lockdown period in German metropolitan areas. After accounting for meteorological effects, PM2.5 concentrations during the spring 2020 lockdown period were 5 % lower compared to the same time period in 2019. However, during the 2020 pre-lockdown period (winter), PM2.5 concentrations with meteorology accounted for were 19 % lower than in 2019. Meanwhile, NO2 concentrations with meteorology accounted for dropped by 23 % during the 2020 lockdown period compared to an only 9 % drop for the 2020 pre-lockdown period, both compared to 2019. SO2 and CO concentrations with meteorology accounted for show no significant changes during the 2020 lockdown period compared to 2019. GEOS-Chem (GC) simulations with a COVID-19 emission reduction scenario based on the observations (23 % reduction in anthropogenic NOx emission with unchanged anthropogenic volatile organic compounds (VOCs) and SO2) are consistent with the small reductions of PM2.5 during the lockdown and are used to identify the underlying drivers for this. Due to being in a NOx-saturated ozone production regime, GC OH radical and O3 concentrations increased (15 % and 9 %, respectively) during the lockdown compared to a business-as-usual (BAU, no lockdown) scenario. Ox (equal to NO2+O3) analysis implies that the increase in ozone at nighttime is solely due to reduced NO titration. The increased O3 results in increased NO3 radical concentrations, primarily during the night, despite the large reductions in NO2. Thus, the oxidative capacity of the atmosphere is increased in all three important oxidants, OH, O3, and NO3. PM nitrate formation from gas-phase nitric acid (HNO3) is decreased during the lockdown as the increased OH concentration cannot compensate for the strong reductions in NO2, resulting in decreased daytime HNO3 formation from the OH + NO2 reaction. However, nighttime formation of PM nitrate from N2O5 hydrolysis is relatively unchanged. This results from the fact that increased nighttime O3 results in significantly increased NO3, which roughly balances the effect of the strong NO2 reductions on N2O5 formation. Ultimately, the only small observed decrease in lockdown PM2.5 concentrations can be explained by the large contribution of nighttime PM nitrate formation, generally enhanced sulfate formation, and slightly decreased ammonium. This study also suggests that high PM2.5 episodes in early spring are linked to high atmospheric ammonia concentrations combined with favorable meteorological conditions of low temperature and low boundary layer height. Northwest Germany is a hot-spot of NH3 emissions, primarily emitted from livestock farming and intensive agricultural activities (fertilizer application), with high NH3 concentrations in the early spring and summer months. Based on our findings, we suggest that appropriate NOx and VOC emission controls are required to limit ozone, and that should also help reduce PM2.5. Regulation of NH3 emissions, primarily from agricultural sectors, could result in significant reductions in PM2.5 pollution.

An Epidemiological Study to Investigate Links between Atmospheric Pollution from Farming and SARS-CoV-2 Mortality.

Exposure to atmospheric particulate matter and nitrogen dioxide has been linked to SARS-CoV-2 infection and death. We hypothesized that long-term exposure to farming-related air pollutants might predispose to an increased risk of COVID-19-related death. To test this hypothesis, we performed an ecological study of five Italian Regions (Piedmont, Lombardy, Veneto, Emilia-Romagna and Sicily), linking all-cause mortality by province (administrative entities within regions) to data on atmospheric concentrations of particulate matter (PM2.5 and PM10) and ammonia (NH3), which are mainly produced by agricultural activities. The study outcome was change in all-cause mortality during March–April 2020 compared with March–April 2015–2019 (period). We estimated all-cause mortality rate ratios (MRRs) by multivariate negative binomial regression models adjusting for air temperature, humidity, international import-export, gross domestic product and population density. We documented a 6.9% excess in MRR (proxy for COVID-19 mortality) for each tonne/km2 increase in NH3 emissions, explained by the interaction of the period variable with NH3 exposure, considering all pollutants together. Despite the limitations of the ecological design of the study, following the precautionary principle, we recommend the implementation of public health measures to limit environmental NH3 exposure, particularly while the COVID-19 pandemic continues. Future studies are needed to investigate any causal link between COVID-19 and farming-related pollution.

Spatiotemporal Distribution of Ammonia Emissions from Poultry Farming in the Yangtze River Delta Based on Online Monitoring Derived Local Emission Factors

In order to obtain the ammonia emission level and space-time distribution characteristics of the poultry production industry in the Yangtze River Delta, an online high-resolution monitoring system was used to continuously monitor the atmospheric ammonia concentration in the breeding house and compost shed in a typical large-scale layer farm. By obtaining the ammonia emission level and emission factor during each growth stage, we established the localized ammonia emission inventory for the poultry production industry in the Yangtze River Delta. The results showed that the average daily ρ(NH3) in the breeding house and compost shed for spring, summer, autumn, and winter were (1.85±0.38), (4.58±0.33), (3.87±0.12), and (2.83±0.47) mg·m-3 and (2.04±0.50), (4.04±1.04), (2.51±0.67), and (1.55±0.16) mg·m-3 respectively. Ammonia emissions showed a significant daily hourly change trend. The highest hourly ammonia concentration in the layer house appeared from 13:00-14:00 in the afternoon, and the minimum appeared from 01:00-03:00 in the morning. The highest hourly ammonia concentration in the compost shed occurred between 16:00-19:00 in summer and autumn, whereas the diurnal changes in spring and winter were not significant. Hourly changes in ammonia emissions during the day were mainly affected by daily temperature, poultry activities, and manure management. Ammonia concentrations at different growth stages of laying hens showed significant differences. ρ (NH3) from young chickens, laying hens, and pre-eliminated chickens were (1.85±0.38), (2.83±0.47), and (1.61±0.32) mg·m-3, respectively. The ammonia emission rate from laying hens reached 1.53 times and 1.65 times that of young chickens and pre-eliminated chickens, respectively. Metabolism levels and feed intake at different growth stages were the main reasons for the differences in ammonia emissions. Ammonia emission factors for the layer house and compost shed in spring, summer, autumn, and winter were (0.13±0.02), (0.54±0.01), (0.39±0.01), and (0.17±0.01) g·(bird·d)-1 and (0.07±0.01), (0.17±0.02), (0.08±0.01), and (0.04±0.01) g·(bird·d)-1, respectively. Annual ammonia emission factors reached (0.11±0.06) kg·(bird·a)-1 and (0.03±0.02) kg·(bird·a)-1, respectively. Our results suggest that ambient temperature, ventilation mode, chicken house type, and manure removal frequency were the main influencing factors of ammonia emissions from poultry production. The uncertainty ranges of the ammonia emission coefficients reached±122%,±79%, and±74%, and±56%, respectively. Great uncertainties were generated when empirical emission factors were used for emission inventory establishment. Based on the results of online monitoring, model simulation, and literature analysis, we established an ammonia emission inventory for the poultry production industry within the Yangtze River Delta region by adopting the emission factors of (0.16±0.08) kg·(bird·a)-1. In 2019, the total ammonia emission from poultry production was (108.81±54.41) kt. In terms of spatial distribution, ammonia emission intensities in the northern regions were significantly higher than those in the southern parts. The ammonia emission intensities during summer were 3.38-3.56 times higher than those in spring and winter.

Mapping gaseous dimethylamine, trimethylamine, ammonia, and their particulate counterparts in marine atmospheres of China’s marginal seas – Part 2: Spatiotemporal heterogeneity, causes, and hypothesis

Abstract. Spatiotemporal heterogeneities in the concentrations of alkaline gases and their particulate counterparts in the marine atmosphere over China's marginal seas were investigated in terms of causes and chemical conversion during two winter cruise campaigns, using semi-continuous measurements made by an onboard URG-9000D Ambient Ion Monitor-Ion Chromatograph (AIM-IC, Thermo Fisher). During the cruise campaign over the East China Sea from 27 December 2019 to 6 January 2020, the concentrations of gas-phase atmospheric trimethylamine (TMAgas) varied by approximately 1 order of magnitude, with an average (± standard deviation) of 0.10±0.04 µg m−3 corresponding to a mixing ratio of 26±17 pptv. Corresponding mean values were 0.037±0.011 µg m−3 (14±5 pptv in mixing ratio) over the Yellow Sea during the period from 7 to 16 January 2020 and 0.031±0.009 µg m−3 (12±4 pptv in mixing ratio) over the Yellow Sea and Bohai Sea from 9 to 22 December 2019. By contrast, the simultaneously observed concentrations of TMA in PM2.5, detected as TMAH+, over the East China Sea were 0.098±0.069 µg m−3 and substantially smaller than the 0.28±0.18 µg m−3 observed over the Yellow Sea and Bohai Sea from 9 to 22 December 2019. A significant correlation between TMAgas and particulate TMAH+ was observed over the East China Sea, but no correlation was found over the Yellow Sea and Bohai Sea. Proportional or disproportional variations in concentrations of TMAgas with particulate TMAH+ over the sea zones were probably attributed to the difference in the enrichment of TMAH+ in the sea surface microlayer. In addition, spatiotemporal heterogeneities in concentrations of atmospheric ammonia (NH3gas), atmospheric dimethylamine (DMAgas), and DMA in PM2.5, detected as DMAH+, were investigated. Case analyses were performed to illustrate the formation and chemical conversion of particulate aminium ions in marine aerosols. Finally, we hypothesized the release of basic gases and particulate counterparts from the ocean to the atmosphere, together with the secondary formation of DMAH+ and chemical conversion of TMAH+, in the marine atmosphere.

Vehicular Emissions Enhanced Ammonia Concentrations in Winter Mornings: Insights from Diurnal Nitrogen Isotopic Signatures.

A general feature in the diurnal cycle of atmospheric ammonia (NH3) concentrations is a morning spike that typically occurs around 07:00 to 10:00 (LST). Current hypotheses to explain this morning's NH3 increase remain elusive, and there is still no consensus whether traffic emissions are among the major sources of urban NH3. Here, we confirmed that the NH3 morning pulse in urban Beijing is a universal feature, with an annual occurrence frequency of 73.0% and a rapid growth rate (>20%) in winter. The stable nitrogen isotopic composition of NH3 (δ15N-NH3) in winter also exhibited a significant diurnal variation with an obvious morning peak at 07:00 to 10:00 (-18.6‰, mass-weighted mean), higher than other times of the day (-26.3‰). This diurnal pattern suggests that a large fraction of NH3 in the morning originated from nonagricultural sources, for example, power plants, vehicles, and coal combustion that tend to have higher δ15N-NH3 emission signatures relative to agricultural emissions. In particular, the contribution from vehicular emissions increased from 18% (00:00 to 07:00) to 40% (07:00 to 10:00), while the contribution of fertilizer sources to NH3 was reduced from 15.8% at 00:00 to 07:00 to 5.2% at 07:00 to 10:00. We concluded that NH3 concentrations in winter mornings in urban Beijing were indeed enhanced by vehicle emissions, which should be considered in air pollution regulations.

Estimating nitrogen risk to Himalayan forests using thresholds for lichen bioindicators

Himalayan forests are biodiverse and support the cultural and economic livelihoods of their human communities. They are bounded to the south by the Indo-Gangetic Plain, which has among the highest concentrations of atmospheric ammonia globally. This source of excess nitrogen pushes northwards into the Himalaya, generating concern that Himalayan forests will be impacted. To estimate the extent to which atmospheric nitrogen is impacting Himalayan forests we focussed on lichen epiphytes, which are a well-established bioindicator for atmospheric nitrogen pollution. First, we reviewed published literature describing nitrogen thresholds (critical levels and loads) at which lichen epiphytes are affected, identifying a mean and confidence intervals based on previous research conducted across a diverse set of biogeographic and ecological settings. Second, we used estimates from previously published atmospheric chemistry models (EMEP-WRF and UKCA-CLASSIC) projected to the Himalaya with contrasting spatial resolution and timescales to characterise model variability. Comparing the lichen epiphyte critical levels and loads with the atmospheric chemistry model projections, we created preliminary estimates of the extent to which Himalayan forests are impacted by excess nitrogen; this equated to c. 80–85% and c. 95–98% with respect to ammonia and total nitrogen deposition, respectively. Recognising that lichens are one of the most sensitive bioindicators for atmospheric nitrogen pollution, our new synthesis of previous studies on this topic generated concern that most Himalayan forests are at risk from excess nitrogen. This is a desk-based study that now requires verification through biological surveillance, for which we provide key recommendations.

Mapping gaseous dimethylamine, trimethylamine, ammonia, and their particulate counterparts in marine atmospheres of China's marginal seas – Part 1: Differentiating marine emission from continental transport

Abstract. To study sea-derived gaseous amines, ammonia, and primary particulate aminium ions in the marine atmosphere of China's marginal seas, an onboard URG-9000D Ambient Ion Monitor-Ion Chromatograph (AIM-IC, Thermo Fisher) was set up on the front deck of the R/V Dongfanghong-3 to semi-continuously measure the spatiotemporal variations in the concentrations of atmospheric trimethylamine (TMAgas), dimethylamine (DMAgas), and ammonia (NH3gas) along with their particulate matter (PM2.5) counterparts. In this study, we differentiated marine emissions of the gas species from continental transport using data obtained from 9 to 22 December 2019 during the cruise over the Yellow and Bohai seas, facilitated by additional short-term measurements collected at a coastal site near the Yellow Sea during the summer, fall, and winter of 2019. The data obtained from the cruise and coastal sites demonstrated that the observed TMAgas and protonated trimethylamine (TMAH+) in PM2.5 over the Yellow and Bohai seas overwhelmingly originated from marine sources. During the cruise, no significant correlation (P>0.05) was observed between the simultaneously measured TMAH+ and TMAgas concentrations. Additionally, the concentrations of TMAH+ in the marine atmosphere varied around 0.28±0.18 µg m−3 (average ± standard deviation), with several episodic hourly average values exceeding 1 µg m−3, which were approximately 1 order of magnitude larger than those of TMAgas (approximately 0.031±0.009 µg m−3). Moreover, there was a significant negative correlation (P<0.01) between the concentrations of TMAH+ and NH4+ in PM2.5. Therefore, the observed TMAH+ in PM2.5 was overwhelmingly derived from primary sea-spray aerosols. Using TMAgas and TMAH+ in PM2.5 as tracers for sea-derived basic gases and sea-spray particulate aminium ions, the values of non-sea-derived DMAgas, NH3gas, and non-sea-spray particulate DMAH+ in PM2.5 were estimated. The estimated average values of each species contributed 16 %, 34 %, and 65 % of the observed average concentrations for non-sea-derived DMAgas, NH3gas, and non-sea-spray particulate DMAH+ in PM2.5, respectively. Uncertainties remained in the estimations, as TMAH+ may decompose into smaller molecules in seawater to varying extents. The non-sea-derived gases and non-sea-spray particulate DMAH+ likely originated from long-range transport from the upwind continents based on the recorded offshore winds and increased concentrations of non-sea-salt SO42- (nss-SO42-) and NH4+ in PM2.5. The lack of a detectable increase in particulate DMAH+, NH4+, and nss-SO42- concentrations in several SO2 plumes did not support the secondary formation of particulate DMAH+ in the marine atmosphere.

Diurnal evolution of total column and surface atmospheric ammonia in the megacity of Paris, France, during an intense springtime pollution episode

Abstract. Ammonia (NH3) is a key precursor for the formation of atmospheric secondary inorganic particles, such as ammonium nitrate and sulfate. Although the chemical processes associated with the gas-to-particle conversion are well known, atmospheric concentrations of gaseous ammonia are still scarcely characterized. However, this information is critical, especially for processes concerning the equilibrium between ammonia and ammonium nitrate, due to the semivolatile character of the latter. This study presents an analysis of the diurnal cycle of atmospheric ammonia during a pollution event over the Paris megacity region in spring 2012 (5 d in late March 2012). Our objective is to analyze the link between the diurnal evolution of surface NH3 concentrations and its integrated column abundance, meteorological variables and relevant chemical species involved in gas–particle partitioning. For this, we implement an original approach based on the combined use of surface and total column ammonia measurements. These last ones are derived from ground-based remote sensing measurements performed by the Observations of the Atmosphere by Solar Infrared Spectroscopy (OASIS) Fourier transform infrared observatory at an urban site over the southeastern suburbs of the Paris megacity. This analysis considers the following meteorological variables and processes relevant to the ammonia pollution event: temperature, relative humidity, wind speed and direction, and the atmospheric boundary layer height (as indicator of vertical dilution during its diurnal development). Moreover, we study the partitioning between ammonia and ammonium particles from concomitant measurements of total particulate matter (PM) and ammonium (NH4+) concentrations at the surface. We identify the origin of the pollution event as local emissions at the beginning of the analyzed period and advection of pollution from Benelux and western Germany by the end. Our results show a clearly different diurnal behavior of atmospheric ammonia concentrations at the surface and those vertically integrated over the total atmospheric column. Surface concentrations remain relatively stable during the day, while total column abundances show a minimum value in the morning and rise steadily to reach a relative maximum in the late afternoon during each day of the spring pollution event. These differences are mainly explained by vertical mixing within the boundary layer, provided that this last one is considered well mixed and therefore homogeneous in ammonia concentrations. This is suggested by ground-based measurements of vertical profiles of aerosol backscatter, used as tracer of the vertical distribution of pollutants in the atmospheric boundary layer. Indeed, the afternoon enhancement of ammonia clearly seen by OASIS for the whole atmospheric column is barely depicted by surface concentrations, as the surface concentrations are strongly affected by vertical dilution within the rising boundary layer. Moreover, the concomitant occurrence of a decrease in ammonium particle concentrations and an increase in gaseous ammonia abundance suggests the volatilization of particles for forming ammonia. Furthermore, surface observations may also suggest nighttime formation of ammonium particles from gas-to-particle conversion, for relative humidity levels higher than the deliquescence point of ammonium nitrate.

Atmospheric Ammonia Measurements Over a Coastal Salt Marsh Ecosystem Along the Mid‐Atlantic U.S.

AbstractMeasurements of atmospheric ammonia (NH3) concentrations and fluxes are limited in coastal regions in the eastern U.S. In this study, continuous and high temporal resolution measurements (5s) of atmospheric NH3 concentrations were recorded using a cavity ring‐down spectrometer in a temperate tidal salt marsh at the St Jones Reserve (Dover, DE). Micrometeorological variables were measured using an eddy covariance system which is part of the AmeriFlux network (US‐StJ). Soil, plant, and water chemistry were also analyzed to characterize the sources and sinks of atmospheric NH3. A new analytical methodology was used to estimate the average ecosystem‐scale diurnal cycle of NH3 fluxes by replicating the characteristics of a chamber experiment. This virtual chamber approach estimates positive surface fluxes in continuing strongly stable conditions when mixing with the air above is minimal. Our findings show that tidal water level may have a significant impact on NH3 emissions from the marsh. The largest fluxes were observed at low tide when more soil was exposed. While it is expected that NH3 fluxes will peak when the air temperature maximizes, high tide occurred concurrently with midday peaks in solar irradiance led to a decrease in NH3 fluxes. Furthermore, soil, plant, and water chemistry measurements underpinning the NH3 concentrations and fluxes lead us to conclude that this coastal wetland ecosystem can act as either a sink or a source of NH3. Such measurements provide novel data on which we can base reliable parameterizations to simulate NH3 emissions from coastal salt marsh ecosystems using surface‐atmosphere transfer models.

Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

Symbolic seasonal variation newly found in atmospheric ammonia concentration in urban area of Japan

The NH3(g) concentration measured at multi-site network in Kobe and Kitakyushu, Japan by using passive method continuously for one year in the late 2000s (September 2008–August 2009) and March 2018–February 2019, respectively, was statistically analyzed from the viewpoint of its controlling factors for temporal variation and spatial distribution. Nine survey sites were established in a region of Kobe, where highly urbanized, agricultural and mountainous areas were located within a 20-km x 20-km region; and one site in Kitakyushu, considered as urbanized and industrialized area, was taken into account. In terms of temporal variation, in both areas of Kobe and Kitakyushu, the NH3(g) concentration indicated lower level in the summer than those in other seasons and experienced higher concentration in colder period, which was newly found compared with the conventional wisdom and results in former studies. Regarding spatial distribution, the NH3(g) concentration showed large variations depending on the site, and the annual mean NH3(g) concentration ranged from 0 ppb (not detected: N.D.) to around 5 ppb. The NH3(g) concentration at the mountainous site with high elevation was the lowest, while it was the highest at the site where the contribution of agriculture was noticeably large in the NH3 inventory, followed by commercial and residential areas. The meteorological factors significantly contributed to the specific seasonal variation; moreover, multiple factors such as located situation, acid-base balance in the atmospheric reaction and vehicular emission were mutually related and presumably responsible for the seasonality of higher in the colder season and lower in the warmer season. When the NH3(g) concentration in the urbanized area is discussed, as in our present study area, the proportion of humans and pets (Human&Pet) to the total in the NH3 inventory could be a good parameter to account for the NH3(g) concentration.