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Abstract 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. Highlights • High-res air pollutant concentrations combined with residence/workplace populations • Exposures to NO 2 , PM 2.5 & O 3 including workplace hours compared with residence only • Population-weighted mean NO 2 exposure 0.3 μg m−3 (2%) higher; less for PM 2.5 and O 3 • Individual exposures vary substantially accounting for home and workplace location. • Greatest spatio-temporal variation when considering exposure to NO 2 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Biosphere carbon sinks are crucial for reducing atmospheric carbon dioxide (CO 2 ) concentration to mitigate global warming, but are substantially affected by the input of reactive nitrogen (N r ). Although the effects of anthropogenic CO 2 emission and nitrogen deposition (indicated by N r emission to atmosphere) on carbon sink have been studied, it is unclear how their ratio (C/N) changes with economic development and how such change alters biosphere carbon sinks. Here, by compiling datasets for 132 countries we find that the C/N ratio continued to increase despite anthropogenic CO 2 and N r emissions to atmosphere both showing an asymmetric para-curve with economic growth. The inflection points of CO 2 and N r emissions are found at around $15,000 gross domestic product per capita worldwide. Economic growth promotes the use of N r and energy, while at the same time increases their use efficiencies, together resulting in occurrences of inflection points of CO 2 and N r emissions. N r emissions increase slower but decrease faster than that of CO 2 emissions before and after the inflection point, respectively. It implies that there will be relatively more anthropogenic CO 2 emission but less N deposition with economic growth. This may limit biosphere carbon sink because of relative shortage of Nr. This finding should be integrated/included in global climate change modelling. Efforts, such as matching N deposition with carbon sequestration on regional scale, to manage CO 2 and N r emissions comprehensively to maintain a balance are critical. [ABSTRACT FROM AUTHOR]

Land-use regression (LUR) models are increasingly used to estimate exposure to air pollution in urban areas. An appropriate monitoring network is an important component in the development of a robust LUR model. In this study concentrations of NO 2 were simulated by a dispersion model at ‘virtual’ monitoring sites in 54 network designs of varying numbers and types of site, using a 25 km 2 area in Edinburgh, UK, as an example location. Separate LUR models were developed for each network. The LUR models were then used to estimate NO 2 concentration at all residential addresses, which were evaluated against the dispersion-modelled concentration at these addresses. The improvement in predictive capability of the LUR models was insignificant above ∼30 monitoring sites, although more sites tended to yield more precise LUR models. Monitoring networks containing sites located within highly populated areas better estimated NO 2 concentrations across all residential locations. LUR models constructed from networks containing more roadside sites better characterised the high end of residential NO 2 concentrations but had increased errors when considering the whole range of concentrations. No particular composition of monitoring network resulted in good estimation simultaneously across all residential NO 2 concentration and of the highest NO 2 levels. This evaluation with dispersion modelling has shown that previous LUR model validation methods may have been optimistic in their assessment of the model's predictive performance at residential locations. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • The cropland NUE in China based on county scale was estimated. • Most counties in China have a NUE ranging between 20% and 40%. • Opposite to vegetables, the higher the share of cereals grown the greater the NUE. • NUE effected by multiple driving factors, not only socio-economic, but also natural. [ABSTRACT FROM AUTHOR]

Anthropogenic activities are responsible for the emission of gaseous and particulate pollutants that modify atmospheric composition. Such changes are, in turn, responsible for the degradation of air quality at the regional/local scale as well as for changes of climate. Air pollution and climate change are two intimately connected environmental issues. However, these two environmental challenges are still viewed as separate issues, which are dealt with by different science communities and within different policy frameworks. Indeed, many mitigation options offer the possibility to both improve air quality and mitigate climate change but, at the same time, mitigation options that may provide benefits to one aspect, are worsening the situation in the other. Therefore, coordinated actions taking into account the air quality-climate linkages are required. These actions need to be based on strong scientific grounds, as recognised by the European Commission that in the past few years has promoted consultation processes among the science community, the policy makers and the relevant stakeholders. Here, the main fields in which such coordinated actions are needed are examined from a policy perspective. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The aim of this work was to compare the variability in an urban area of fine particles (PM 2.5 ), ultrafine particles (UFP) and black carbon (BC) and to evaluate the relationship between each particle metric and potential factors (local traffic, street topography and synoptic meteorology) contributing to the variability. Concentrations of the three particle metrics were quantified using portable monitors through a combination of mobile and static measurements in the city of Edinburgh, UK. The spatial variability of UFP and BC was large, of similar magnitude and about 3 times higher than the spatial variability of PM 0.5-2.5 (the PM size fraction actually quantified in this work). Highest inter-daily variability was observed for PM 0.5-2.5 , which was approximately 2 times higher than inter-daily variability of BC and UFP. Elevated concentrations of UFP and BC were observed along streets with high traffic volumes whereas PM 0.5-2.5 showed less variation between streets and a footpath without road traffic. Both BC and UFP were significantly correlated with traffic counts, while no significant correlation between PM 0.5-2.5 and traffic counts was observed. BC was significantly correlated with UFP, with significantly different regression slopes between working days and non-working days implying that the increased number of diesel powered heavy goods vehicles during working days contributed more to BC than to UFP. It is concluded that variations in BC and UFP concentrations were mainly determined by the nearby traffic count and varying background concentrations between days, while variation in PM 0.5-2.5 concentration was mainly associated with regional sources. These findings imply the need for different policies for managing human exposure to these different particle components: control of much BC and UFP appears to be manageable at local scale by restricting traffic emissions; however, abatement of PM 2.5 requires a more strategic approach, in cooperation with other regions and countries on emissions control to curb long-range transport of PM 2.5 precursors. [ABSTRACT FROM AUTHOR]

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 PM 2.5 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. [ABSTRACT FROM AUTHOR]

In this virtual thematic issue (VTI) the authors of 14 papers address key challenges of environmental modelling and software to support the identification of human and ecological health risks. The contributions address different pathways how environmental exposure can affect human health with a focus on models, data and software and can be divided into the following research areas: (1) modelling approaches to quantify air pollution concentrations and exposure, (2) models and methods to determine health effects of air pollution, (3) models and software to predict and quantify disease and health risks and (4) data interoperability and integration. These contributions highlight that further advances in this research field are required, especially from highly polluted regions, as so far papers from these regions are scarce. The majority of contributions covers exposure to ambient air pollution, which is a key public health risk in both industrialised and developing countries. While not a focus of this VTI, human exposure to water and soil contamination as well as exposure pathways through other environmental media are equally relevant. Further research into how modelling, software and data can support an integrated assessment of the whole Exposome is therefore essential. [ABSTRACT FROM AUTHOR]

Abstract: 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 &y& Elsevier]

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 km2 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. [Display omitted] • Mean atmospheric N r deposition was 36 kg N ha−1 yr−1 in a subtropical catchment in a 2-yr study. • Total N r emissions in catchment were 80 kg N ha−1 yr−1, with 62 kg N ha−1 yr−1 from NH 3 emissions. • The net N r budget showed high emissions due to NH 3 emissions from livestock and fertilization. • Paddy and tea fields were net sources of N r s, while forest was a net strong sink of N r s. Both atmospheric emissions and depositions of Nrs were high, and the net budget showed high emissions in a typical agricultural catchment in subtropical central China. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • A empirical model of NH 3 emissions from croplands was established. • Two emission peaks are found in April and October following the fertilization. • Total emission was estimated at 4.3 Tg NH 3 yr−1 in 2017 with an emission factor of 12%. • More emission hotspots were found in South China due to warming climate. The highly spatio-temporal resolution NH 3 emission inventory from cropland fertilization was developed by an empirical regression model in 2853 counties of China. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, crucial aspects of the implications and the complexity of interconnected multi-pollutant multi-effect assessments of both air pollution control strategies and the closely related reduction of greenhouse gas emissions will be discussed. The main aims of the work described here are to identify the core problems which occur when trying to apply current state-of-the-art methodology to conduct integrated assessments – in this context, cost-benefit assessment (CBA) as well as cost-effectiveness assessment (CEA) – using sophisticated computer models and propose solutions to the problems identified. The approaches described will display the integrated use of databases, efficient algorithms and already existing software tools and models in a unified model framework. The first part of the paper discusses the need for new developments in one particular field of Integrated Assessment Models (IAMs), which is the use of (typically) country-specific single pollutant abatement cost curves, which have been applied in a large number of modelling approaches with the aim to find cost-effective solutions for given air quality targets. However, research conducted to find such cost-effective solutions for the non-linear problem of tropospheric ozone abatement (dealing with two primary pollutants and their rather complex relationship to form tropospheric ozone, [see] [Friedrich, R., Reis, S. (Eds.), 2000. Tropospheric Ozone Abatement – Developing Efficient Strategies for the Reduction of Ozone Precursor Emissions in Europe. Springer Publishers] identified basic problems of cost curve based approaches even in this two-pollutant case. The approach discussed here promises to solve the key problems identified, making extensive use of databases in order to provide fast and high quality model input for CEA and CBA. In addition to that, the application of Genetic Algorithms will be discussed as a means to address extremely complex, vast solution spaces which are typical for the tasks IAMs are set to solve nowadays. As the application of the model in extensive assessment studies is currently under way, it is yet too early for a full evaluation of lessons learned. However, initial tests of performance and behaviour have shown robust and promising results. [Copyright &y& Elsevier]

Synthetic nitrogen (N) fertilizers support global food production and feed over half of the global population. However, more than half of the N fertilizers applied to croplands are not absorbed by crops, but lost to the environment, leading to low N use efficiency (NUE) globally. Identifying and overcoming socioeconomic barriers to achieve an improvement of NUE and a reduction in N loss is thus key for N management and to attain agricultural and environmental sustainability. In this paper, we compiled the global cropland N budgets at a national scale (1961–2018) and developed robust econometric models to explore the relationship between cropland N use with socioeconomic factors. The results demonstrate that economic development and farm size are the key drivers to improve NUE for agricultural and environmental sustainability. In less developed countries, it is difficult for farmers to access chemical fertilizers, leading to croplands receiving too little N input and at a high NUE, but suffering from soil N depletion. As economic development progresses, more fertilizer is produced and applied, but smallholder farming typically leads to over-fertilization and consequently N losses to the environment. Large-scale farming improves NUE, reduces N loss and benefits agricultural production and environmental protection. Also, interactions between farm size and economic development, international trade, crop and livestock systems, and related policies are important causes for changes in the NUE of the whole agricultural system. Overcoming these socioeconomic barriers especially combining large-scale farming could effectively reduce excessive N inputs and sustain agricultural and environmental N management, while maintaining food production, resulting in a triple-win for food security, poverty alleviation, and environmental protection. • Overcoming socio-economic barriers is vital to achieve N sustainability. • Economy and farm size are key drivers of sustaining agriculture and environment. • Large-scale farming improves NUE and benefit environmental protection. • Farm size interacted with economy, crop-livestock systems, and policies affect NUE. [ABSTRACT FROM AUTHOR]

Abstract: Science in general and modelling in particular provide in-depth understanding of environmental processes and clearly demonstrate the present unsustainable use of resources on a global scale. The latest report by the Intergovernmental Panel on Climate Change (IPCC), for instance, shows that climate is changing and with a 95% certainty it is the humans have caused the change. The future climatic conditions are shown to be largely adversely affecting human wellbeing on this planet. Yet we see in numerous examples that societies are very slow in reacting to this rapid depletion of natural resources. What still seems lacking is the translation of scientific reports and the results of analysis and modelling into corrective actions. We argue that one of the reasons for this is the traditional workflow of environmental modelling, which starts with the purpose, the goal formulation, and ends with problem solutions or decision support tools. Instead, modelling, and applied science in general, has to enhance its scope beyond the problem solving stage, to do more on the problem definition and solution implementation phases. Modelling can be also used for identification of societal values and for setting purposes by appropriate communication of the modelling process and results. We believe this new approach for modelling can impact and bring the social values to the forefront of socio-environmental debate and hence turn scientific results into actions sooner rather than later. Instead of being separated from the modelling process, the translation of results should be an intrinsic part of it. We discuss several challenges for recent socio-environmental modelling and conclude with ten propositions that modellers and scientists in general can follow to improve their communication with the society and produce results that can be understood and used to improve awareness and education and spur action. [Copyright &y& Elsevier]

To feed an increasingly affluent population, the nitrogen input into global food production systems is currently two times the safe planetary boundary leading to adverse impacts on the local and global environments. The nitrogen footprint is an important index to understand the impact of human activities on the environment, however, it is rarely applied at a watershed scale. By using the C oupled H uman A nd N atural S ystem (CHANS) model, it was found that the total nitrogen input to the Lake Tai watershed has increased from 141.1 Gg N yr−1 in 1995 to 244.3 Gg N yr−1 in 2010, and then decreased again to 201.2 Gg N yr−1 in 2015. The study findings are consistent with the change in the total nitrogen concentration observed in Lake Tai. While the per capita nitrogen footprint remained stable at around 30 kg N yr−1 before 2010, a substantial decrease to approximately 25 and 20 kg N yr−1 in 2010 and 2015, respectively, has occurred. Dominant sources of nitrogen emissions contributing to the nitrogen footprint gradually have changed from agricultural production to wastewater and nitrogen oxides emissions from fossil fuel combustion. A reduction of the nitrogen footprint is beneficial for effective nitrogen pollution control strategies and better wastewater treatment techniques should be prioritized for future policymaking. • The nitrogen footprint has been reduced in the Lake Tai watershed. • The nitrogen footprint can link water pollution and human activities. • Urban areas have become new hotspots of the nitrogen footprint for Lake Tai. • Optimization of the nitrogen footprint of urban areas can achieve sustainable development in the watershed. [ABSTRACT FROM AUTHOR]

Abstract Farm size plays a critical role in agricultural sustainability. This may have far-reaching consequences for the economic and environmental performance of agricultural production, resulting, for instance, in an excessive use of mineral fertilizers. However, the magnitude of such effects and their main causes are not well understood, while being essential for effective policy development, especially for countries like China where the agricultural sector is still largely dominated by smallholder farms. In this paper, we review the current understanding of how farm size affects agricultural sustainability using China's crop farming as an example from economic, environment and social aspects. We analyze impacts from both a Chinese and a global perspective to identify intervention points to improve agricultural performance. We found that increasing farm size has a positive impact on farmer's net profit, as well as economic, technical and labor efficiency with mean coefficients of 0.005, 0.02 and 2.25, respectively. Nevertheless, the relationships between farm size and overall productivity, total factor productivity and allocative efficiency are still not well understood and therefore require more research. Meanwhile, increase in farm size is associated with statistically significant decrease in fertilizer and pesticide use per hectare, showing clear benefits for environmental protection. In line with the experiences documented for the evolution of agricultural practices in developed countries, the expansion of large-scale farming is a critical path for modernizing agricultural production and ensuring sustainable food production from the social perspective. Measures concerning farm size should be implemented in an interaction between farmers and the government to promote the green development of agriculture. Highlights • Farm size plays an important role in the performance of agriculture. • Increasing farm size shows clear benefits for environmental protection. • Large-scale farming is a critical path for modernizing and sustaining agriculture. • Smallholders prefer to use more non-fixed inputs to increase yields. [ABSTRACT FROM AUTHOR]

Abstract 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. Graphical abstract Unlabelled Image Highlights • Concerns positive public health impacts of urban nature's cultural ecosystem services (CES). • Discusses global development trends' implications for the provision and demand of CES. • Discusses current research and key research questions for a new research agenda. [ABSTRACT FROM AUTHOR]

• We show how reduced form and complex models can be applied in combination to inform air pollution policy development. • We compare PM 2.5 concentrations calculated by both a reduced-form and a complex ACTM, showing good agreement. • Both models agree well with observations of PM 2.5 and SIA concentrations from national monitoring networks. • We present this comparison for the current (2018) and selected future (2040) emissions scenarios in the United Kingdom. • We confirm the robustness of a reduced-form model to evaluate alternative futures, through comparison with an Eulerian ACTM. 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. [ABSTRACT FROM AUTHOR]

• Life course air pollution exposure and biological ageing markers were investigated in 525 older adults. • Young-to-middle adulthood exposure was associated with higher Horvath DNAmAge. • In males, air pollution in middle adulthood was linked to shorter DNAm telomere length. • Air pollution around birth was associated with shorter DNAm telomere length among females. 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

Optimal nitrogen (N) management is critical for efficient crop production and agricultural pollution control. Approximate 210–220 kg ha−1 N fertilizer was applied in millions of small plots through broadcasting way in China, resulting in over and loss of N fertilizers. However, it is difficult to implement advanced management practices on smallholder farms due to a lack of knowledge. Here, using 35,502 on-farm fertilization experiments, we demonstrated that smallholders in China could actually produce more grain with less N fertilizer use only through optimizing N application rate. The yields of wheat, maize and rice were shown to increase between 10% and 19% while N application rates were reduced by 15–19%. These changes resulted in an increase in N use efficiency (NUE) by 32–46% and a reduction in N surplus by 40% without actually changing farmers' operational practices. By reducing N application rates in line with official recommendations would not only save fertilizer cost while increasing crop yield, but also at the same time reduce environmental N pollution in China. Beyond of optimizing N application rate, improved management practices were required to produce more grain with less pollution, which would need about 11.8 billion US dollars for the implementation and reducing N loss reduction by 1.75 million tons to the environment. [Display omitted] • Optimizing N fertilizer rate was estimated based on 35,502 field experiments nationally. • Optimizing N rate increased NUE by 32–46% with 40% lower N surplus. • Environmental N loss was predicted to be reduced by 5.06 million t by optimizing N rate. • Best management strategies could result in 1.75 million tons N loss reduction. [ABSTRACT FROM AUTHOR]

Abstract: 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 &y& Elsevier]

The atmospheric chemistry and deposition model has been applied for calculation of nitrogen and sulphur depositions to the entire North Sea area for the year 1999. The total atmospheric nitrogen and sulphur depositions to the North Sea area were determined to 709 kton (kt) N and 551 kt S, respectively. Since the North Sea area was calculated to be 747,988 km2, this is equivalent to an average deposition of 0.9 ton N km−2 and 0.7 ton S km−2, respectively. The depositions decrease strongly from the south end (about 2–3 kt N km−2) to the north end (about 0.2 kt N km−2) of the North Sea, due to increasing distance to the large source areas in the northern part of the European continent. The territorial waters of Belgium, the Netherlands and Germany receive about 50% higher deposition densities than the average value for the entire North Sea area. For the remaining territorial waters of the North Sea the depositions follow more or less the fraction of the area. The results furthermore show that about 60% of the total nitrogen deposition is related to emissions from combustion sources (nitrogen oxides) and about 40% from emissions related to agricultural activities (ammonia). [Copyright &y& Elsevier]