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Cropland fragmentation contributes to low productivity and high abandonment risk. Using spatial statistics on a detailed land use map, we show that 10% of Chinese croplands have no potential to be consolidated for large-scale farming (>10 ha) owing to spatial constraints. These fragmented croplands contribute only 8% of total crop production while using 15% of nitrogen fertilizers, leading to 12% of fertilizer loss in China. Optimizing the cropping structure of fragmented croplands to meet animal food demand in China can increase animal food supply by 19%, equivalent to increasing cropland proportionally. This crop-switching approach would lead to a 10% and 101% reduction in nitrogen and greenhouse gas emissions, respectively, resulting in a net benefit of US$ 7 billion yr -1 . If these fragmented croplands were relocated to generate large-scale farming units, livestock, vegetable and fruit production would be increased by 8%, 3% and 14%, respectively, and reactive nitrogen and greenhouse gas emissions would be reduced by 16% and 5%, respectively, resulting in a net benefit of US$ 44 billion yr -1 . Both solutions could be used to achieve synergies between food security, economic benefits and environmental protection through increased agricultural productivity, without expanding the overall cropland area., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Over the past decade, China has experienced a decline in atmospheric reactive nitrogen (Nr) emissions. Given that China's subtropical region is a significant nitrogen (N) deposition hotspot, it is essential to accurately quantify the ten-year variations in dry and wet N depositions in the context of reductions in atmospheric Nr emissions. Here, we evaluated the spatiotemporal variation in N deposition on forest, paddy field and tea field ecosystems in a typical subtropical agricultural catchment from 2011 to 2020. Our findings indicated a significant decrease in total N deposition in both the tea field ecosystem (41.5-30.5 kg N ha -1 ) and the forest ecosystem (40.8-25.7 kg N ha -1 ) (P < 0.05), but no significant change in the paddy field ecosystem (29.3-32.9 kg N ha -1 ). Specifically, dry N deposition exhibited significant declines except in the paddy field ecosystem, whereas wet N deposition had no significant change. The reduction in total oxidized and reduced N depositions in forest and tea field ecosystems is attributed to the decrease in NO x and NH 3 emissions. Additionally, The ratio of NH x deposition to total N deposition all exceeded 0.5 in three ecosystems and the NH x /NO y ratio had an increasing trend (P < 0.05) in the paddy field, indicating that reactive N emissions from agricultural sources were the primary contributor to overall N deposition. Our study emphasizes that despite the decreasing trend in N deposition, it still exceeds the critical loads of natural ecosystems and requires stringent N emissions control, particularly from agricultural sources, in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH 3 , NO x and N 2 O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$ 61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on., (© 2024. The Author(s).)

Maintaining food production while reducing agricultural nitrogen pollution is a grand challenge under global climate change. Yet, the response of global agricultural nitrogen uses and losses to climate change on the temporal and spatial scales has not been fully characterized. Here, using historical data for 1961-2018 from over 150 countries, we show that global warming leads to small temporal but substantial spatial impacts on cropland nitrogen use and losses. Yield and nitrogen use efficiency increase in 29% and 56% of countries, respectively, whereas they reduce in the remaining countries compared with the situation without global warming in 2018. Precipitation and farm size changes would further intensify the spatial variations of nitrogen use and losses globally, but managing farm size could increase the global cropland nitrogen use efficiency to over 70% by 2100. Our results reveal the importance of reducing global inequalities of agricultural nitrogen use and losses to sustain global agriculture production and reduce agricultural pollution., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Rapid demographic ageing substantially affects socioeconomic development 1-4 and presents considerable challenges for food security and agricultural sustainability 5-8 , which have so far not been well understood. Here, by using data from more than 15,000 rural households with crops but no livestock across China, we show that rural population ageing reduced farm size by 4% through transferring cropland ownership and land abandonment (approximately 4 million hectares) in 2019, taking the population age structure in 1990 as a benchmark. These changes led to a reduction of agricultural inputs, including chemical fertilizers, manure and machinery, which decreased agricultural output and labour productivity by 5% and 4%, respectively, further lowering farmers' income by 15%. Meanwhile, fertilizer loss increased by 3%, resulting in higher pollutant emissions to the environment. In new farming models, such as cooperative farming, farms tend to be larger and operated by younger farmers, who have a higher average education level, hence improving agricultural management. By encouraging the transition to new farming models, the negative consequences of ageing can be reversed. Agricultural input, farm size and farmer's income would grow by approximately 14%, 20% and 26%, respectively, and fertilizer loss would reduce by 4% in 2100 compared with that in 2020. This suggests that management of rural ageing will contribute to a comprehensive transformation of smallholder farming to sustainable agriculture in China., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Mental health is influenced by multiple complex and interacting genetic, psychological, social, and environmental factors. As such, developing state-of-the-art mental health knowledge requires collaboration across academic disciplines, including environmental science. To assess the current contribution of environmental science to this field, a scoping review of the literature on environmental influences on mental health (including conditions of cognitive development and decline) was conducted. The review protocol was developed in consultation with experts working across mental health and environmental science. The scoping review included 202 English-language papers, published between 2010 and 2020 (prior to the COVID-19 pandemic), on environmental themes that had not already been the subject of recent systematic reviews; 26 reviews on climate change, flooding, air pollution, and urban green space were additionally considered. Studies largely focused on populations in the USA, China, or Europe and involved limited environmental science input. Environmental science research methods are primarily focused on quantitative approaches utilising secondary datasets or field data. Mental health measurement was dominated by the use of self-report psychometric scales. Measures of environmental states or exposures were often lacking in specificity (e.g., limited to the presence or absence of an environmental state). Based on the scoping review findings and our synthesis of the recent reviews, a research agenda for environmental science's future contribution to mental health scholarship is set out. This includes recommendations to expand the geographical scope and broaden the representation of different environmental science areas, improve measurement of environmental exposure, prioritise experimental and longitudinal research designs, and giving greater consideration to variation between and within communities and the mediating pathways by which environment influences mental health. There is also considerable opportunity to increase interdisciplinarity within the field via the integration of conceptual models, the inclusion of mixed methods and qualitative approaches, as well as further consideration of the socio-political context and the environmental states that can help support good mental health. The findings were used to propose a conceptual model to parse contributions and connections between environmental science and mental health to inform future studies.

Nitrogen use efficiency (NUE, defined as the fraction of N input harvested as product) is an important indicator to understand nitrogen use and losses in croplands as an element of determining sustainable food production. China, as the country with the largest amount of nitrogen fertilizer use globally, research into NUE consistently finds it to be much lower than that in developed countries. Understanding the driving forces of the underlying causes of this low NUE is thus crucial to improve nitrogen use and reduce losses in China. Here we applied the CHANS model to estimate cropland NUE for over 2800 counties in China for the year 2017. Results showed that in most counties NUE ranged between 20% and 40%, while an NUE >50% was mainly found in Northeastern China, likely as a result of large-scale, modern agriculture operations. The source of N input and crop types significantly affected NUE in our assessment. Nitrogen deposition, straw recycling, and biological nitrogen fixation (BNF) could improve NUE, while chemical nitrogen fertilizer and manure inputs reduce NUE. Grain crops have a much higher NUE compared to vegetables, which are often over-fertilized. Moreover, NUE in Southern China is strongly influenced by natural factors such as temperature and precipitation. Specifically, NUE in the Yangtze River Delta (eastern coastal region of China) is associated with socio-economic factors including GDP and the degree of urbanization, while in North-central China, NUE is mainly determined by nitrogen input sources. These examples illustrate that approaches aiming at improving NUE need to be location-specific with consideration of multiple natural and socioeconomic factors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM 2.5 , primary PM 2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Ruminants have lower feed use efficiency than monogastric livestock, and produce higher reactive nitrogen and methane emissions, but can utilize human-inedible biomass through foraging and straw feedstock. Here we conduct a counterfactual analysis, replacing ruminants with monogastric livestock to quantify the changes in nitrogen loss and greenhouse gas emissions globally from a whole life cycle perspective. Switching 12% of global livestock production from monogastric to ruminant livestock could reduce nitrogen emissions by 2% and greenhouse gas emissions by 5% due to land use change and lower demand for cropland areas for ruminant feed. The output from released cropland could feed up to 525 million people worldwide. More ruminant products, in addition to optimized management, would generate overall benefits valued at US$468 billion through reducing adverse impacts on human and ecosystem health, and mitigating climate impacts., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored., Objective and Methods: Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations., Results: We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM 2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits., Conclusion: Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2022. Published by Elsevier Inc. All rights reserved.)

Background: Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing., Methods: Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM 2.5 ), sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants., Results: We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM 2.5 , SO 2 and NO 2 ., Discussion: We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Farm size affects nitrogen fertilizer input and agricultural practices, which are key determinants of ammonia (NH 3 ) emissions from croplands. However, the degree to which NH 3 emissions are associated with changes in farm size is not well understood yet despite its crucial role in achieving agricultural sustainability in China, where agricultural production is still dominated by smallholder farms. Here we provide a first analysis of the relationship between farm size and NH 3 emissions based on 863 000 surveys conducted in 2017 across China. Results show that NH 3 emissions (kg ha -1 ) on average decrease by 0.07% for each 1% increase in average farm size. This change occurs mainly due to a reduction in nitrogen fertilizer use and the introduction of more efficient fertilization practices. The largest reduction in NH 3 emissions is found in maize, with less pronounced changes in rice cultivation, and none for wheat production. Overall lower NH 3 emissions factors can be observed in the north of China with increasing farm size, especially in the northeast, the opposite pattern was found in the south. National total NH 3 emissions could be approximately halved (1.5 Tg) in a scenario favoring a conversion to large-scale farming systems. This substantial reduction potential highlights the potential of such a transition to reduce NH 3 emissions, including benefits from a socioeconomic point of view as well as for improving air quality.

Nearly one quarter of global meat production occurs in China, but a lack of detailed spatial livestock production data hinders ongoing pollution mitigation strategies. Here we generate high-resolution maps of livestock systems in China using over 480,000 farm surveys from 2007 to 2017, finding that China produced more livestock protein with fewer animals and less total pollution impact through better breeding, feeding and manure management in large-scale livestock farms. Hotspots of production can be observed across the North China Plain, Northeastern China and the Sichuan Basin. The Clean Water Act reduced manure nutrient losses to water by one third, but with limited changes to methane and ammonia emissions. Integrated production and consumption abatement measures costing approximately US$6 billion could further reduce livestock pollution by 2050, realizing benefits of up to US$30 billion due to avoided human health and ecosystem costs., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

China's agriculture is dominated by smallholder farms, which have become major sources of negative environmental impacts including eutrophication, formation of haze, soil acidification and greenhouse gas emissions. To mitigate these environmental impacts, new farming models including family farming, cooperation farming and industrial farming have emerged in recent years. However, whether these new farming practices would improve the economic and environmental performance as compared to the current smallholder farming has yet to be verified on ground level. In this paper, by using pilot farming cases within the watershed of Tai Lake, we found that alternative farming models produced 7% more crop yield, while using 8% less fertilizer, leading to a 28% decrease in pollutant emission per hectare. These alternative farming models have a 17% higher fertilizer use efficiency and 50% higher profit per hectare. Compared to smallholder farming, these alternative farming practices invest 27% more resources into agricultural facilities, including advanced machinery, and have a younger, better educated labor force as a consequence of a larger farm size and more specialization. These input changes substantially increase fertilizer use efficiency and reduce agricultural pollution. Policy arrangements to support and facilitate the uptake of these farming models will further promote the green development and sustainable intensification of agricultural production., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Freshwater is a scarce resource, and maintaining water quality is of great importance in dryland Australia. How water quality is affected by the dry climate and socio-economic influences in Australia remains widely unknown. Here, we find that agriculture activity dominates reactive nitrogen (N r ) emissions to water bodies. Such emissions not only contribute to deteriorating water quality in Southeastern Australia but also harm marine ecosystems, including the Great Barrier Reef, a World Natural Heritage site. A dry and warm climate reduces the share of N r emitted directly to water bodies; however, it increases the N r concentration in surface water due to reduced water volume, leading to a 3-fold higher water N r concentration compared to major rivers globally, e.g., in the US or China. Business-as-usual socioeconomic development would increase the total N r emitted to surface water by at least 43% by 2050, while effective mitigation measures could reduce N runoff by about 27%. Advanced agricultural management strategies should be considered to reduce future environmental pressures due to N runoff in Australia.

China's agricultural sector is dominated by smallholder farms, which mostly exhibit relatively low nutrient use efficiency, low agricultural income and substantial non-point-source pollution. Here we assess the spatial feasibility and cost-effectiveness of agricultural land consolidation in China by integrating data from over 40,000 rural surveys, ecological modelling and geostatistical analysis. We found that 86% of Chinese croplands could be consolidated to establish a large-scale farming regime with an average field size greater than 16 ha. This would result in a 59% and 91% increase in knowledge exchange and machinery use, respectively, contributing to a 24% reduction in total nitrogen input, an 18% increase in nitrogen use efficiency and a 39% reduction in labour requirement, while doubling labour income. Despite requiring a one-time investment of approximate US$370 billion for land consolidation, total agricultural profits would double due to agricultural production costs being halved., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

The study of emissions and depositions of atmospheric reactive nitrogen species (N r s) in a region is important to uncover the sources and sinks of atmospheric N r s in the region. In this study, atmospheric total N r s depositions including both wet-only and dry deposition were monitored simultaneously across major land-use types in a 105 km 2 catchment called Jinjing River Catchment (JRC) in subtropical central China from 2015 to 2016. Based on activity data and emission factors for the main N r s emission sources, ammonia (NH 3 ) and nitrogen oxides (NO x ) emission inventories for the catchment were also compiled. The estimated total N r s deposition in JRC was 35.9 kg N ha -1 yr -1 , with approximately 49.7 % attributed to reduced compounds (NH x ), and 40.5 % attributed to oxidized (NO y ). The total N r s emission rate in JRC was 80.4 kg N ha -1 yr -1 , with 61.5 and 18.9 kg N ha -1 yr -1 from NH 3 and NO x emissions, respectively. Livestock excretion and fertilization were the two main contributing emission sources for NH 3 , while vehicle sources contributed the bulk of NO x emissions. The net atmospheric budgets of N r s in paddy field, forest, and tea field were +3.7, -36.1, and +23.8 kg N ha -1 yr -1 , respectively. At the catchment scale, the net atmospheric budget of N r s was +47.7 kg N ha -1 yr -1 , with +43.7 kg N ha -1 yr -1 of NH x and +4.0 kg N ha -1 yr -1 of NO y, indicating that the subtropical catchment was net sources of atmospheric N r s. Considering that excessive atmospheric N r emissions and deposition may cause adverse effects on the environment, effects should be conducted to mitigate the N r s emissions from agriculture and transportation, and increasing the area of forest is good for reducing the net positive budget of atmospheric N r s in the subtropical catchments in China., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Ammonia (NH 3 ) volatilization is one of the main pathways of nitrogen loss from cropland, resulting not only in economic losses, but also environmental and human health impacts. The magnitude and timing of NH 3 emissions from cropland fertilizer application highly depends on agricultural practices, climate and soil factors, which previous studies have typically only considered at coarse spatio-temporal resolution. In this paper, we describe a first highly detailed empirical regression model for ammonia (ERMA) emissions based on 1443 field observations across China. This model is applied at county level by integrating data with unprecedented high spatio-temporal resolution of agricultural practices and climate and soil factors. Results showed that total NH 3 emissions from cropland fertilizer application amount to 4.3 Tg NH 3 yr -1 in 2017 with an overall NH 3 emission factor of 12%. Agricultural production for vegetables, maize and rice are the three largest emitters. Compared to previous studies, more emission hotspots were found in South China and temporally, emission peaks are estimated to occur three months earlier in the year, while the total amount of emissions is estimated to be close to that calculated by previous studies. A second emission peak is identified in October, most likely related to the fertilization of the second crop in autumn. Incorporating these new findings on NH 3 emission patterns will enable a better parametrization of models and hence improve the modelling of air quality and subsequent impacts on ecosystems through reactive N deposition., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Cropland ammonia (NH 3 ) emission is a critical driver triggering haze pollution. Many agricultural policies were enforced in past four decades to improve nitrogen (N) use efficiency while maintaining crop yield. Inadvertent reductions of NH 3 emissions, which may be induced by such policies, are not well evaluated. Here, we quantify the China's cropland-NH 3 emission change from 1980 to 2050 and its response to policy interventions, using a data-driven model and a survey-based dataset of the fertilization scheme. Cropland-NH 3 emission in China doubled from 1.93 to 4.02 Tg NH 3 -N in period 1980-1996, and then decreased to 3.50 Tg NH 3 -N in 2017. The prevalence of four agricultural policies may avoid ~3.0 Tg NH 3 -N in 2017, mainly located in highly fertilized areas. Optimization of fertilizer management and food consumption could mitigate three-quarters of NH 3 emission in 2050 and lower NH 3 emission intensity (emission divided by crop production) close to the European Union and the United States. Our findings provide an evidence on the decoupling of cropland-NH 3 from crop production in China and suggest the need to achieve cropland-NH 3  mitigation while sustaining crop yields in other developing economies., (© 2021 John Wiley & Sons Ltd.)

Australia is a warm country with well-developed agriculture and a highly urbanized population. How these specific features impact the nitrogen cycle, emissions, and consequently affect environmental and human health is not well understood. Here, we find that the ratio of reactive nitrogen ( N r ) losses to air over losses to water in Australia is 1.6 as compared to values less than 1.1 in the USA, the European Union, and China. Australian N r emissions to air increased by more than 70% between 1961 and 2013, from 1.2 Tg N yr -1 to 2.1 Tg N yr -1 . Previous emissions were substantially underestimated mainly due to neglecting the warming climate. The estimated health cost from atmospheric N r emissions in Australia is 4.6 billion US dollars per year. Emissions of N r to the environment are closely correlated with economic growth, and reduction of N r losses to air is a priority for sustainable development in Australia., Competing Interests: The authors declare no competing interests., (Copyright © 2021 Yi Sun et al.)

Urbanization has often been considered a threat to food security since it is likely to reduce the availability of croplands. Using spatial statistics and scenario analysis, we show that an increase in China's urbanization level from 56% in 2015 to 80% in 2050 would actually release 5.8 million hectares of rural land for agricultural production-equivalent to 4.1% of China's total cropland area in 2015. Even considering the relatively lower land fertility of these new croplands, crop production in 2050 would still be 3.1-4.2% higher than in 2015. In addition, cropland fragmentation could be reduced with rural land release and a decrease in rural population, benefiting large-scale farming and environmental protection. To ensure this, it is necessary to adopt an integrated urban-rural development model, with reclamation of lands previously used as residential lots. These insights into the urbanization and food security debate have important policy implications for global regions undergoing rapid urbanization., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Reducing ammonia (NH 3 ) volatilization from croplands while satisfying the food demand is strategically required to mitigate haze pollution. However, the global pattern of NH 3 volatilization remains uncertain, primarily because of the episodic nature of NH 3 volatilization rates and the high variation of fertilization practices. Here, we improve a global estimate of crop-specific NH 3 emissions at a high spatial resolution using an updated data-driven model with a survey-based dataset of the fertilization scheme. Our estimate of the globally averaged volatilization rate (12.6% ± 2.1%) is in line with previous data-driven studies (13.7 ± 3.1%) but results in one-quarter lower emissions than process-based models (16.5 ± 3.1%). The associated global emissions are estimated at 14.4 ± 2.3 Tg N, with more than 50% of the total stemming from three stable crops or 12.2% of global harvested areas. Nearly three-quarters of global cropland-NH 3 emissions could be reduced by improving fertilization schemes (right rate, right type, and right placement). A small proportion (20%) of global harvested areas, primarily located in China, India, and Pakistan, accounts for 64% of abatement potentials. Our findings provide a critical reference guide for the future abatement strategy design when considering locations and crop types.

Digital technology is having a major impact on many areas of society, and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists, and representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency, and reproducibility in science. The perspective also includes a call to build an international community working in this important area., Competing Interests: Both G.B. and T.H. are on the advisory board of Patterns. The authors declare no other competing interests., (© 2020 The Authors.)

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 (β = -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.

Epidemiological studies on the health effects of air pollution usually rely on measurements from fixed ground monitors, which provide limited spatio-temporal coverage. Data from satellites, reanalysis, and chemical transport models offer additional information used to reconstruct pollution concentrations at high spatio-temporal resolutions. This study aims to develop a multi-stage satellite-based machine learning model to estimate daily fine particulate matter (PM 2.5 ) levels across Great Britain between 2008-2018. This high-resolution model consists of random forest (RF) algorithms applied in four stages. Stage-1 augments monitor-PM 2.5 series using co-located PM 10 measures. Stage-2 imputes missing satellite aerosol optical depth observations using atmospheric reanalysis models. Stage-3 integrates the output from previous stages with spatial and spatio-temporal variables to build a prediction model for PM 2.5 . Stage-4 applies Stage-3 models to estimate daily PM 2.5 concentrations over a 1 km grid. The RF architecture performed well in all stages, with results from Stage-3 showing an average cross-validated R 2 of 0.767 and minimal bias. The model performed better over the temporal scale when compared to the spatial component, but both presented good accuracy with an R 2 of 0.795 and 0.658, respectively. These findings indicate that direct satellite observations must be integrated with other satellite-based products and geospatial variables to derive reliable estimates of air pollution exposure. The high spatio-temporal resolution and the relatively high precision allow these estimates (approximately 950 million points) to be used in epidemiological analyses to assess health risks associated with both short- and long-term exposure to PM 2.5 ., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

To feed an increasingly affluent population, reactive nitrogen (Nr) inputs to China's lands and waters have substantially increased over the past century. Today, China's Nr emissions account for over one third of global total emissions, leading to serious environmental pollution and health damages. Quantifying the spatial variability of Nr inputs is crucial for the identification of intervention points to mitigate Nr pollution, which, however, is not well known. Here, we present a database describing Nr inputs to China for the year 2017 with a 1 km × 1 km resolution, considering land use and Nr sources, compiled by using the CHANS model. Results show that the North China Plain, the Sichuan Basin and the Middle-Lower Yangtze River Plain are hotspots of Nr inputs, where per hectare Nr input is an order of magnitude higher than that in other regions. Cropland and surface water bodies receive much higher Nr inputs than other land use types. This unique database will provide basic data for research on environmental health and global change modelling.

The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM 2.5 , 30% (22%) for SO 2 , 24% (19%) for NH 3 and 15% (13%) for O 3 , compared with a desert scenario. By contrast, urban vegetation reduces average urban PM 2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM 2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO 2 are small, and urban tree planting is even forecast to increase urban NO 2 and NO x concentrations, due to the chemical interaction with changes in BVOC emissions and O 3 , but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost-benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Purpose of Review: The literature on air pollution and brain health is rapidly expanding and it is a universal finding that greater exposure to air pollution is associated with worse outcomes, whatever the measure of brain health used (clinical dementia, neuroimaging correlates, or cognitive impairment). However, there are a number of important questions which the studies currently published are not able to answer: when in the life course does exposure to air pollution most have the most impact?; which pollutant(s) or components are most important?; and since dementia describes a heterogeneous group of conditions, which is most affected by exposure to air pollution?, Recent Findings: We briefly review and discuss the nine articles which have been published so far in 2018, so recently that they were not included in the four review articles also published this year. We highlight the variation in estimates of air pollution used but the consistency in deriving them from residential address (with or without some knowledge of an individual's previous home locations)., Summary: We are now at the stage when the research agenda needs to be agreed and we believe these three questions should be the focus of future research.

Urbanization is a global trend, and consequently the quality of urban environments is increasingly important for human health and wellbeing. Urban life-style is typically associated with low physical activity and sometimes with high mental stress, both contributing to an increasing burden of diseases. Nature-based solutions that make effective use of ecosystem services, particularly of cultural ecosystem services (CES), can provide vital building blocks to address these challenges. This paper argues that, the salutogenic, i.e. health-promoting effects of CES have so far not been adequately recognised and deserve more explicit attention in order to enhance decision making around health and wellbeing in urban areas. However, a number of research challenges will need to be addressed to reveal the mechanisms, which underpin delivery of urban CES. These include: causal chains of supply and demand, equity, and equality of public health benefits promoted. Methodological challenges in quantifying these are discussed. The paper is highly relevant for policy makers within and beyond Europe, and also serves as a review for current researchers and as a roadmap to future short- and long-term research opportunities., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Managing reactive nitrogen (N r ) to achieve a sustainable balance between production of food, feed and fiber, and environmental protection is a grand challenge in the context of an increasingly affluent society. Here, we propose a novel framework for national nitrogen (N) assessments enabling a more consistent comparison of the uses, losses and impacts of N r between countries, and improvement of N r management for sustainable development at national and regional scales. This framework includes four key components: national scale N budgets, validation of N fluxes, cost-benefit analysis and N r management strategies. We identify four critical factors for N r management to achieve the sustainable development goals: N use efficiency (NUE), N r recycling ratio (e.g., ratio of livestock excretion applied to cropland), human dietary patterns and food waste ratio. This framework was partly adopted from the European Nitrogen Assessment and now is successfully applied to China, where it contributed to trigger policy interventions toward improvements for future sustainable use of N r . We demonstrate how other countries can also benefit from the application our framework, in order to include sustainable N r management under future challenges of growing population, hence contributing to the achievement of some key sustainable development goals (SDGs).

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 NO 2 , PM 2.5 and O 3 . 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 NO 2 , with an estimated 0.3 μg m -3 (equivalent to 2%) increase in population-weighted annual exposure to NO 2 across the whole UK population. Population-weighted exposure to PM 2.5 and O 3 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 NO 2 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., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Asthma has a considerable, but potentially, avoidable burden on many populations globally. Scotland has some of the poorest health outcomes from asthma. Although ambient pollution, weather changes and sociodemographic factors have been associated with asthma attacks, it remains unclear whether modelled environment data and geospatial information can improve population-based asthma predictive algorithms. We aim to create the afferent loop of a national learning health system for asthma in Scotland. We will investigate the associations between ambient pollution, meteorological, geospatial and sociodemographic factors and asthma attacks., Methods and Analysis: We will develop and implement a secured data governance and linkage framework to incorporate primary care health data, modelled environment data, geospatial population and sociodemographic data. Data from 75 recruited primary care practices (n=500 000 patients) in Scotland will be used. Modelled environment data on key air pollutants at a horizontal resolution of 5 km×5 km at hourly time steps will be generated using the EMEP4UK atmospheric chemistry transport modelling system for the datazones of the primary care practices' populations. Scottish population census and education databases will be incorporated into the linkage framework for analysis. We will then undertake a longitudinal retrospective observational analysis. Asthma outcomes include asthma hospitalisations and oral steroid prescriptions. Using a nested case-control study design, associations between all covariates will be measured using conditional logistic regression to account for the matched design and to identify suitable predictors and potential candidate algorithms for an asthma learning health system in Scotland.Findings from this study will contribute to the development of predictive algorithms for asthma outcomes and be used to form the basis for our learning health system prototype., Ethics and Dissemination: The study received National Health Service Research Ethics Committee approval (16/SS/0130) and also obtained permissions via the Public Benefit and Privacy Panel for Health and Social Care in Scotland to access, collate and use the following data sets: population and housing census for Scotland; Scottish education data via the Scottish Exchange of Data and primary care data from general practice Data Custodians. Analytic code will be made available in the open source GitHub website. The results of this study will be published in international peer reviewed journals., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Reliable detection and attribution of changes in nitrogen (N) runoff from croplands are essential for designing efficient, sustainable N management strategies for future. Despite the recognition that excess N runoff poses a risk of aquatic eutrophication, large-scale, spatially detailed N runoff trends and their drivers remain poorly understood in China. Based on data comprising 535 site-years from 100 sites across China's croplands, we developed a data-driven upscaling model and a new simplified attribution approach to detect and attribute N runoff trends during the period of 1990-2012. Our results show that N runoff has increased by 46% for rice paddy fields and 31% for upland areas since 1990. However, we acknowledge that the upscaling model is subject to large uncertainties (20% and 40% as coefficient of variation of N runoff, respectively). At national scale, increased fertilizer application was identified as the most likely driver of the N runoff trend, while decreased irrigation levels offset to some extent the impact of fertilization increases. In southern China, the increasing trend of upland N runoff can be attributed to the growth in N runoff rates. Our results suggested that increased SOM led to the N runoff rate growth for uplands, but led to a decline for rice paddy fields. In combination, these results imply that improving management approaches for both N fertilizer use and irrigation is urgently required for mitigating agricultural N runoff in China., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The fast economic development of southwest China has resulted in significant increases in the concentrations of reactive nitrogen (Nr) in the atmosphere. In this study, an urban (Chengdu, CD), suburban (Shifang, SF) and agriculture (Yanting, YT) - dominated location in the Sichuan Province, southwest China, were selected to investigate the atmospheric composition of Nr, their concentrations and deposition rates. We measured Nr concentrations in precipitation (NH 4 + , NO 3 - and organic N (DON)), the gas phase (NH 3 and NO 2 ), and the aerosol particles (PM 2.5 ), and calculated their fluxes over a two year period (2014-2016). Total annual N deposition rates were 49.2, 44.7 and 19.8 kg N ha -1 yr -1 at CD, SF and YT, respectively. Ammonia concentrations were larger at the urban and suburban sites than the agricultural site (12.2, 14.9, and 4.9 μg N m -3 at CD, SF and YT, respectively). This is consistent with the multitude of larger sources of NH 3 , including city garbage, livestock and traffic, in the urban and suburban areas. Monthly NO 2 concentrations were lower in warmer compared to the colder months, but seasonal differences were insignificant. Daily PM 2.5 concentrations ranged from 7.7 to 236.0, 5.0-210.4 and 4.2-128.4 μg m -3 at CD, SF and YT, respectively, and showed significant correlations with fine particulate NH 4 + and NO 3 - concentrations. Ratios of reduced to oxidized N were in the range of 1.6-2.7. This implies that the control of reduced Nr especially in urban environments is needed to improve local air quality., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The impacts of climate on health and wellbeing occur in time and space and through a range of indirect, complicated mechanisms. This diversity of pathways has major implications for national public health planning and influence on interventions that might help to mitigate and adapt to rapidly changing environmental conditions, nationally and internationally. This paper draws upon evidence from public health and adverse impact studies across climate science, hydrology, agriculture, public health, and the social sciences. It presents a conceptual model to support decision-making by recognizing both the proximal and distal pathways from climate-induced environmental change to national health and wellbeing. The proximal and distal pathways associated with food security, migration and mobility illustrate the diverse climate change influences in different geographic locations over different timescales. We argue that greater realization and articulation of proximal and distal pathways should radically alter how climate change is addressed as a national and international public health challenge.

China is a global hotspot of atmospheric ammonia (NH 3 ) emissions and, as a consequence, very high nitrogen (N) deposition levels are documented. However, previous estimates of total NH 3 emissions in China were much lower than inference from observed deposition values would suggest, highlighting the need for further investigation. Here, we reevaluated NH 3 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 NH 3 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 NH 3 emission rates from mineral fertilizer application and livestock having been underestimated previously. Our estimated NH 3 emission levels are consistent with the measured deposition of NH x (including NH 4 + and NH 3 ) on land (11-14 Tg N yr -1 ) and the substantial increases in NH 3 concentrations observed by satellite measurements over China. These findings substantially improve our understanding on NH 3 emissions, implying that future air pollution control strategies have to consider the potentials of reducing NH 3 emission in China.

Urban air quality in China has been declining substantially in recent years due to severe haze episodes. The reduction of sulfur dioxide (SO 2 ) and nitrogen oxide (NO x ) emissions since 2013 does not yet appear to yield substantial benefits for haze mitigation. As the reductions of those key precursors to secondary aerosol formation appears not to sufficient, other crucial factors need to be considered for the design of effective air pollution control strategies. Here we argue that ammonia (NH 3 ) plays a - so far - underestimated role in the formation of secondary inorganic aerosols, a main component of urban fine particulate matter (PM 2.5 ) concentrations in China. By analyzing in situ concentration data observed in major cities alongside gridded emission data obtained from remote sensing and inventories, we find that emissions of NH 3 have a more robust association with the spatiotemporal variation of PM 2.5 levels than emissions of SO 2 and NO x . As a consequence, we argue that urban PM 2.5 pollution in China in many locations is substantially affected by NH 3 emissions. We highlight that more efforts should be directed to the reduction of NH 3 emissions that help mitigate PM 2.5 pollution more efficiently than other PM 2.5 precursors. Such efforts will yield substantial co-benefits by improving nitrogen use efficiency in farming systems. As a consequence, such integrated strategies would not only improve urban air quality, but also contribute to China's food-security goals, prevent further biodiversity loss, reduce greenhouse gas emissions and lead to economic savings., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing 'Big Data' and, more importantly, make the vital step from 'Big Data' to 'Big Information'. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example.

Adverse health effects from exposure to air pollution are a global challenge and of widespread concern. Recent high ambient concentration episodes of air pollutants in European cities highlighted the dynamic nature of human exposure and the gaps in data and knowledge about exposure patterns. In order to support health impact assessment it is essential to develop a better understanding of individual exposure pathways in people's everyday lives by taking account of all environments in which people spend time. Here we describe the development, validation and results of an exposure method applied in a study conducted in Scotland. A low-cost particle counter based on light-scattering technology - the Dylos 1700 was used. Its performance was validated in comparison with equivalent instruments (TEOM-FDMS) at two national monitoring network sites (R(2)=0.9 at a rural background site, R(2)=0.7 at an urban background site). This validation also provided two functions to convert measured PNCs into calculated particle mass concentrations for direct comparison of concentrations with equivalent monitoring instruments and air quality limit values. This study also used contextual and time-based activity data to define six microenvironments (MEs) to assess everyday exposure of individuals to short-term PM2.5 concentrations. The Dylos was combined with a GPS receiver to track movement and exposure of individuals across the MEs. Seventeen volunteers collected 35 profiles. Profiles may have a different overall duration and structure with respect to times spent in different MEs and activities undertaken. Results indicate that due to the substantial variability across and between MEs, it is essential to measure near-complete exposure pathways to allow for a comprehensive assessment of the exposure risk a person encounters on a daily basis. Taking into account the information gained through personal exposure measurements, this work demonstrates the added value of data generated by the application of low-cost monitors., (Copyright © 2014. Published by Elsevier B.V.)

An atmospheric chemical transport model was adapted to simulate the concentration and deposition of heavy metals (arsenic, cadmium, chromium, copper, lead, nickel, selenium, vanadium, and zinc) in the United Kingdom. The model showed that wet deposition was the most important process for the transfer of metals from the atmosphere to the land surface. The model achieved a good correlation with annually averaged measurements of metal concentrations in air. The correlation with measurements of wet deposition was less strong due to the complexity of the atmospheric processes involved in the washout of particulate matter which were not fully captured by the model. The measured wet deposition and air concentration of heavy metals were significantly underestimated by the model for all metals (except vanadium) by factors between 2 and 10. These results suggest major missing sources of annual heavy metal emissions which are currently not included in the official inventory. Primary emissions were able to account for only 9%, 21%, 29%, 21%, 36%, 7% and 23% of the measured concentrations for As, Cd, Cr, Cu, Ni, Pb and Zn. A likely additional contribution to atmospheric heavy metal concentrations is the wind driven re-suspension of surface dust still present in the environment from the legacy of much higher historic emissions. Inclusion of two independent estimates of emissions from re-suspension in the model was found to give an improved agreement with measurements. However, an accurate estimate of the magnitude of re-suspended emissions is restricted by the lack of measurements of metal concentrations in the re-suspended surface dust layer., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

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.

Global nitrogen fixation contributes 413 Tg of reactive nitrogen (Nr) to terrestrial and marine ecosystems annually of which anthropogenic activities are responsible for half, 210 Tg N. The majority of the transformations of anthropogenic Nr are on land (240 Tg N yr(-1)) within soils and vegetation where reduced Nr contributes most of the input through the use of fertilizer nitrogen in agriculture. Leakages from the use of fertilizer Nr contribute to nitrate (NO3(-)) in drainage waters from agricultural land and emissions of trace Nr compounds to the atmosphere. Emissions, mainly of ammonia (NH3) from land together with combustion related emissions of nitrogen oxides (NOx), contribute 100 Tg N yr(-1) to the atmosphere, which are transported between countries and processed within the atmosphere, generating secondary pollutants, including ozone and other photochemical oxidants and aerosols, especially ammonium nitrate (NH4NO3) and ammonium sulfate (NH4)2SO4. Leaching and riverine transport of NO3 contribute 40-70 Tg N yr(-1) to coastal waters and the open ocean, which together with the 30 Tg input to oceans from atmospheric deposition combine with marine biological nitrogen fixation (140 Tg N yr(-1)) to double the ocean processing of Nr. Some of the marine Nr is buried in sediments, the remainder being denitrified back to the atmosphere as N2 or N2O. The marine processing is of a similar magnitude to that in terrestrial soils and vegetation, but has a larger fraction of natural origin. The lifetime of Nr in the atmosphere, with the exception of N2O, is only a few weeks, while in terrestrial ecosystems, with the exception of peatlands (where it can be 10(2)-10(3) years), the lifetime is a few decades. In the ocean, the lifetime of Nr is less well known but seems to be longer than in terrestrial ecosystems and may represent an important long-term source of N2O that will respond very slowly to control measures on the sources of Nr from which it is produced.

Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information., (Copyright © 2012 Elsevier B.V. All rights reserved.)