Urban nitrogen budgets: Evaluating and comparing the path of nitrogen through cities for improved management.

Reactive nitrogen (Nr) released to the environment is a cause of multiple environmental threats. While Nr flows are often only analyzed in an agricultural context, consumption and emission takes place in the urban environment, and opportunities for Nr recycling and effective policy implementation for mitigation often appear in cities. Since little information is available on the bigger picture of Nr flows through the urban environment, these opportunities often remain unexploited. Here we developed a framework to model Nr pathways through urban and surrounding areas, which we applied to four test areas (Beijing and Shijiazhuang (China), Vienna (Austria), and Zielona Góra (Poland)). Using indicators such as recycling rates and Nr surplus, we estimated environmental risks and recycling potentials based on Nr flows and their entry and exit points. Our findings show marked differences between the core and surrounding areas of each city, with the former being a site of Nr consumption with largest flows associated with households, and the latter a site of (agricultural) production with largest flows associated with industry (fertilizers) and urban plants. As a result, Nr transgresses the core areas in a rather linear manner with only 0-5 % being re-used, with inputs from Nr contained in food and fuels and outputs most commonly as non-reactive N2 emissions to the atmosphere from wastewater treatment and combustion processes. While the peri-urban areas show a higher Nr recycling rate (6-14 %), Nr accumulation and emissions from cultivated land pose significant environmental challenges, indicating the need for mitigation measures. We found potential to increase nitrogen use efficiency through improved Nr management on cultivated areas and to increase Nr recycling using urine and sewage sludge as synthetic fertilizer substitutes. Hence our framework for urban nitrogen budgets not only allows for consistent budgeting but helps identify common patterns, potentially harmful flows and Nr recycling potential.

Asthma symptoms, spirometry and air pollution exposure in schoolchildren in an informal settlement and an affluent area of Nairobi, Kenya.

BACKGROUND: Although 1 billion people live in informal (slum) settlements, the consequences for respiratory health of living in these settlements remain largely unknown. This study investigated whether children living in an informal settlement in Nairobi, Kenya are at increased risk of asthma symptoms. METHODS: Children attending schools in Mukuru (an informal settlement in Nairobi) and a more affluent area (Buruburu) were compared. Questionnaires quantified respiratory symptoms and environmental exposures; spirometry was performed; personal exposure to particulate matter (PM2.5) was estimated. RESULTS: 2373 children participated, 1277 in Mukuru (median age, IQR 11, 9-13 years, 53% girls), and 1096 in Buruburu (10, 8-12 years, 52% girls). Mukuru schoolchildren were from less affluent homes, had greater exposure to pollution sources and PM2.5. When compared with Buruburu schoolchildren, Mukuru schoolchildren had a greater prevalence of symptoms, 'current wheeze' (9.5% vs 6.4%, p=0.007) and 'trouble breathing' (16.3% vs 12.6%, p=0.01), and these symptoms were more severe and problematic. Diagnosed asthma was more common in Buruburu (2.8% vs 1.2%, p=0.004). Spirometry did not differ between Mukuru and Buruburu. Regardless of community, significant adverse associations were observed with self-reported exposure to 'vapours, dusts, gases, fumes', mosquito coil burning, adult smoker(s) in the home, refuse burning near homes and residential proximity to roads. CONCLUSION: Children living in informal settlements are more likely to develop wheezing symptoms consistent with asthma that are more severe but less likely to be diagnosed as asthma. Self-reported but not objectively measured air pollution exposure was associated with increased risk of asthma symptoms.

Life Course Air Pollution Exposure and Cognitive Decline: Modelled Historical Air Pollution Data and the Lothian Birth Cohort 1936.

BACKGROUND: Air pollution has been consistently linked with dementia and cognitive decline. However, it is unclear whether risk is accumulated through long-term exposure or whether there are sensitive/critical periods. A key barrier to clarifying this relationship is the dearth of historical air pollution data. OBJECTIVE: To demonstrate the feasibility of modelling historical air pollution data and using them in epidemiologicalmodels. METHODS: Using the EMEP4UK atmospheric chemistry transport model, we modelled historical fine particulate matter (PM2.5) concentrations for the years 1935, 1950, 1970, 1980, and 1990 and combined these with contemporary modelled data from 2001 to estimate life course exposure in 572 participants in the Lothian Birth Cohort 1936 with lifetime residential history recorded. Linear regression and latent growth models were constructed using cognitive ability (IQ) measured by the Moray House Test at the ages of 11, 70, 76, and 79 years to explore the effects of historical air pollution exposure. Covariates included sex, IQ at age 11 years, social class, and smoking. RESULTS: Higher air pollution modelled for 1935 (when participants would have been in utero) was associated with worse change in IQ from age 11-70 years (ß = -0.006, SE = 0.002, p = 0.03) but not cognitive trajectories from age 70-79 years (p > 0.05). There was no support for other critical/sensitive periods of exposure or an accumulation of risk (all p > 0.05). CONCLUSION: The life course paradigm is essential in understanding cognitive decline and this is the first study to examine life course air pollution exposure in relation to cognitive health.

Alkaline air: changing perspectives on nitrogen and air pollution in an ammonia-rich world.

Ammonia and ammonium have received less attention than other forms of air pollution, with limited progress in controlling emissions at UK, European and global scales. By contrast, these compounds have been of significant past interest to science and society, the recollection of which can inform future strategies. Sal ammoniac (nushadir, nao sha) is found to have been extremely valuable in long-distance trade (ca AD 600-1150) from Egypt and China, where 6-8 kg N could purchase a human life, while air pollution associated with nushadir collection was attributed to this nitrogen form. Ammonia was one of the keys to alchemy-seen as an early experimental mesocosm to understand the world-and later became of interest as 'alkaline air' within the eighteenth century development of pneumatic chemistry. The same economic, chemical and environmental properties are found to make ammonia and ammonium of huge relevance today. Successful control of acidifying SO2 and NOx emissions leaves atmospheric NH3 in excess in many areas, contributing to particulate matter (PM2.5) formation, while leading to a new significance of alkaline air, with adverse impacts on natural ecosystems. Investigations of epiphytic lichens and bog ecosystems show how the alkalinity effect of NH3 may explain its having three to five times the adverse effect of ammonium and nitrate, respectively. It is concluded that future air pollution policy should no longer neglect ammonia. Progress is likely to be mobilized by emphasizing the lost economic value of global N emissions ($200 billion yr-1), as part of developing the circular economy for sustainable nitrogen management. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Nitrous oxide emission factors of mineral fertilisers in the UK and Ireland: A Bayesian analysis of 20 years of experimental data.

In this study, we analysed datasets of N2O emission factors (EFs) from 21 separate studies carried out on arable and managed grasslands across the UK and Ireland over the past 20 years. A total of 641 separate events were collated from 40 experimental field sites. Individual EFs ranged over an order of magnitude (0-12% of applied N) for each fertiliser type, following a log-normal distribution in all cases. Our study shows that a Bayesian approach can provide a robust statistical method that is capable of performing uncertainty analysis on log-normal distributed data in a more defensible manner than conventional statistical methods allow. This method allowed for a national scale comparison of EFs between the most commonly applied mineral fertilisers based solely on previously published data (UK and Ireland in this case). The study shows that ammonium nitrate (AN) and Calcium ammonium nitrate (CAN) are the largest emitting fertiliser types by mass across the British Isles (temperate climate zone), with EFs of 1.1 (1.0-1.2) % and 1.0 (0.7-1.3) % for all recorded events, respectively; however, emissions from AN applications were significantly lower for applications to arable fields (0.6%) than to grasslands (1.3%). EFs associated with urea (CO(NH2)2) were significantly lower than AN for grasslands with an EF of 0.6 (0.5-0.7) %, but slightly higher for arable fields with an EF of 0.7 (0.4-1.4) %. The study highlights the potential effectiveness of microbial inhibitors at reducing emissions of N2O from mineral fertilisers, with Dicyandiamide (DCD) treated AN reducing emissions by approximately 28% and urea treated with either DCD or N-(n)-butyl) thiophosphorictriamide (NBTP) reducing emissions by approximately 40%. Although limited by a relatively small sample size (n = 11), urea treated with both DCD and NBPT appeared to have the lowest EF of all treatments at 0.13 (0.08-0.21) %, highlighting the potential to significantly reduce N2O emissions at regional scales if applied instead of conventional nitrogen fertilisers.

What is the most ecologically-meaningful metric of nitrogen deposition?

Nitrogen (N) deposition poses a severe risk to global terrestrial ecosystems, and managing this threat is an important focus for air pollution science and policy. To understand and manage the impacts of N deposition, we need metrics which accurately reflect N deposition pressure on the environment, and are responsive to changes in both N deposition and its impacts over time. In the UK, the metric typically used is a measure of total N deposition over 1-3 years, despite evidence that N accumulates in many ecosystems and impacts from low-level exposure can take considerable time to develop. Improvements in N deposition modelling now allow the development of metrics which incorporate the long-term history of pollution, as well as current exposure. Here we test the potential of alternative N deposition metrics to explain vegetation compositional variability in British semi-natural habitats. We assembled 36 individual datasets representing 48,332 occurrence records in 5479 quadrats from 1683 sites, and used redundancy analyses to test the explanatory power of 33 alternative N metrics based on national pollutant deposition models. We find convincing evidence for N deposition impacts across datasets and habitats, even when accounting for other large-scale drivers of vegetation change. Metrics that incorporate long-term N deposition trajectories consistently explain greater compositional variance than 1-3 year N deposition. There is considerable variability in results across habitats and between similar metrics, but overall we propose that a thirty-year moving window of cumulative deposition is optimal to represent impacts on plant communities for application in science, policy and management.

The influence of residential and workday population mobility on exposure to air pollution in the UK.

Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of air pollutants at the residential address of the study population are representative for overall exposure. This introduces potential bias in the quantification of human health effects. Our study combines new UK Census data comprising information on workday population densities, with high spatio-temporal resolution air pollution concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic estimates of population exposure to NO2, PM2.5 and O3. We explicitly allocated workday exposures for weekdays between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday location into account had the most pronounced impact on potential exposure to NO2, with an estimated 0.3 µg m-3 (equivalent to 2%) increase in population-weighted annual exposure to NO2 across the whole UK population. Population-weighted exposure to PM2.5 and O3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants. We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO2 exposure for these individuals were considerably higher than for the total UK population average when including their workday location. Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution.

Quantifying gross vs. net agricultural land use change in Great Britain using the Integrated Administration and Control System.

Land use change has impacts upon many natural processes, and is one of the key measures of anthropogenic disturbance on ecosystems. Agricultural land covers 70% of Great Britain's (GB) land surface and annually undergoes disturbance and change through farming practices such as crop rotation, ploughing and the planting and subsequent logging of forestry. It is important to quantify how much of GB's agricultural land undergoes such changes and what those changes are at an annual temporal resolution. Integrated Administration and Control System (IACS) data give annual snapshots of agricultural land use at the field level, allowing for high resolution spatiotemporal land use change studies at the national scale. Crucially, not only do the data allow for simple net change studies (total area change of a land use, in a specific areal unit) but also for gross change calculations (summation of all changes to and from a land use), meaning that both gains and losses to and from each land use category can be defined. In this study we analysed IACS data for GB from 2005 to 2013, and quantified gross change for over 90% of the agricultural area in GB for the first time. It was found that gross change totalled 63,500 km2 in GB compared to 20,600 km2 of net change, i.e. the real year-on-year change is, on average, three times larger than net change. This detailed information on nature of land use change allows for increased accuracy in modelling the impact of land use change on ecosystem processes and is directly applicable across EU member states, where collection of such survey data is a requirement. The modelled carbon flux associated with gross land use change was at times >100 Gg C y-1 larger than that based on net land use change for some land use transitions.

Mapping Portuguese Natura 2000 sites in risk of biodiversity change caused by atmospheric nitrogen pollution.

In this paper, we assess and map the risk that atmospheric nitrogen (atN) pollution poses to biodiversity in Natura 2000 sites in mainland Portugal. We first review the ecological impacts of atN pollution on terrestrial ecosystems, focusing on the biodiversity of Natura 2000 sites. These nature protection sites, especially those located within the Mediterranean Basin, are under-characterized regarding the risk posed by atN pollution. We focus on ammonia (NH3) because this N form is mostly associated with agriculture, which co-occurs at or in the immediate vicinity of most areas of conservation interest in Portugal. We produce a risk map integrating NH3 emissions and the susceptibility of Natura 2000 sites to atN pollution, ranking habitat sensitivity to atN pollution using expert knowledge from a panel of Portuguese ecological and habitat experts. Peats, mires, bogs, and similar acidic and oligotrophic habitats within Natura 2000 sites (most located in the northern mountains) were assessed to have the highest relative risk of biodiversity change due to atN pollution, whereas Natura 2000 sites in the Atlantic and Mediterranean climate zone (coastal, tidal, and scrubland habitats) were deemed the least sensitive. Overall, results allowed us to rank all Natura 2000 sites in mainland Portugal in order of evaluated risk posed by atN pollution. The approach is of great relevance for stakeholders in different countries to help prioritize site protection and to define research priorities. This is especially relevant in countries with a lack of expertise to assess the impacts of nitrogen on biodiversity and can represent an important step up from current knowledge in such countries.

Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK.

This paper describes an agricultural model (Roth-CNP) that estimates carbon (C), nitrogen (N) and phosphorus (P) pools, pool changes, their balance and the nutrient fluxes exported from arable and grassland systems in the UK during 1800-2010. The Roth-CNP model was developed as part of an Integrated Model (IM) to simulate C, N and P cycling for the whole of UK, by loosely coupling terrestrial, hydrological and hydro-chemical models. The model was calibrated and tested using long term experiment (LTE) data from Broadbalk (1843) and Park Grass (1856) at Rothamsted. We estimated C, N and P balance and their fluxes exported from arable and grassland systems on a 5km×5km grid across the whole of UK by using the area of arable of crops and livestock numbers in each grid and their management. The model estimated crop and grass yields, soil organic carbon (SOC) stocks and nutrient fluxes in the form of NH4-N, NO3-N and PO4-P. The simulated crop yields were compared to that reported by national agricultural statistics for the historical to the current period. Overall, arable land in the UK have lost SOC by -0.18, -0.25 and -0.08MgCha-1y-1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24MgCha-1y-1 during 1800-1950, 1950-1970 and 1970-2010 simulated in this study. Simulated N loss (by leaching, runoff, soil erosion and denitrification) increased both under arable (-15, -18 and -53kgNha-1y-1) and grass (-18, -22 and -36kgNha-1y-1) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1kgPha-1y-1 under arable and 2.8, 11.3 and 3.6kgPha-1y-1 under grass lands 1800-1950, 1950-1970 and 1970-2010.

Ammonia Emissions May Be Substantially Underestimated in China.

China is a global hotspot of atmospheric ammonia (NH3) emissions and, as a consequence, very high nitrogen (N) deposition levels are documented. However, previous estimates of total NH3 emissions in China were much lower than inference from observed deposition values would suggest, highlighting the need for further investigation. Here, we reevaluated NH3 emissions based on a mass balance approach, validated by N deposition monitoring and satellite observations, for China for the period of 2000 to 2015. Total NH3 emissions in China increased from 12.1 ± 0.8 Tg N yr-1 in 2000 to 15.6 ± 0.9 Tg N yr-1 in 2015 at an annual rate of 1.9%, which is approximately 40% higher than existing studies suggested. This difference is mainly due to more emission sources now having been included and NH3 emission rates from mineral fertilizer application and livestock having been underestimated previously. Our estimated NH3 emission levels are consistent with the measured deposition of NHx (including NH4+ and NH3) on land (11-14 Tg N yr-1) and the substantial increases in NH3 concentrations observed by satellite measurements over China. These findings substantially improve our understanding on NH3 emissions, implying that future air pollution control strategies have to consider the potentials of reducing NH3 emission in China.

Ammonia emissions from an anaerobic digestion plant estimated using atmospheric measurements and dispersion modelling.

Anaerobic digestion (AD) is becoming increasingly implemented within organic waste treatment operations. The storage and processing of large volumes of organic wastes through AD has been identified as a significant source of ammonia (NH3) emissions, however the totality of ammonia emissions from an AD plant have not been previously quantified. The emissions from an AD plant processing food waste were estimated through integrating ambient NH3 concentration measurements, atmospheric dispersion modelling, and comparison with published emission factors (EFs). Two dispersion models (ADMS and a backwards Lagrangian stochastic (bLS) model) were applied to calculate emission estimates. The bLS model (WindTrax) was used to back-calculate a total (top-down) emission rate for the AD plant from a point of continuous NH3 measurement downwind from the plant. The back-calculated emission rates were then input to the ADMS forward dispersion model to make predictions of air NH3 concentrations around the site, and evaluated against weekly passive sampler NH3 measurements. As an alternative approach emission rates from individual sources within the plant were initially estimated by applying literature EFs to the available site parameters concerning the chemical composition of waste materials, room air concentrations, ventilation rates, etc. The individual emission rates were input to ADMS and later tuned by fitting the simulated ambient concentrations to the observed (passive sampler) concentration field, which gave an excellent match to measurements after an iterative process. The total emission from the AD plant thus estimated by a bottom-up approach was 16.8±1.8mgs(-1), which was significantly higher than the back-calculated top-down estimate (7.4±0.78mgs(-1)). The bottom-up approach offered a more realistic treatment of the source distribution within the plant area, while the complexity of the site was not ideally suited to the bLS method, thus the bottom-up method is believed to give a better estimate of emissions. The storage of solid digestate and the aerobic treatment of liquid effluents at the site were the greatest sources of NH3 emissions.

Nutrient fluxes from domestic wastewater: A national-scale historical perspective for the UK 1800-2010.

Nutrient emissions in human waste and wastewater effluent fluxes from domestic sources are quantified for the UK over the period 1800-2010 based on population data from UK Census returns. The most important drivers of change have been the introduction of the water closet (flush toilet) along with population growth, urbanization, connection to sewer, improvements in wastewater treatment and use of phosphorus in detergents. In 1800, the population of the UK was about 12 million and estimated emissions in human waste were 37kt N, 6.2kt P and 205ktorganicC/year. This would have been recycled to land with little or no sewage going directly to rivers or coastal waters. By 1900, population had increased to 35.6 million and some 145kt N were emitted in human waste but, with only the major urban areas connected to sewers, only about 19kt N were discharged in sewage effluent. With the use of phosphorus in detergents, estimated phosphorus emissions peaked at around 63.5ktP/year in the 1980s, with about 28ktP/year being discharged in sewage effluent. By 2010, population had increased to 63 million with estimated emissions of 263kt N, 43.6kt P and 1460ktorganicC/year, and an estimated effluent flux of 104kt N, 14.8kt P and 63kt organic C. Despite improvements in wastewater treatment, current levels of nutrient fluxes in sewage effluent are substantially higher than those in the early 20th century.

Heterogeneity of atmospheric ammonia at the landscape scale and consequences for environmental impact assessment.

We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

Towards a climate-dependent paradigm of ammonia emission and deposition.

Existing descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.