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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.

Producing more food with less pollution and greenhouse gas emissions is a grand challenge for the 21st century. Strategies to successfully promote win‐win outcomes for both food security and environmental health are not easy to identify. Here we comprehensively assess an ecological rice‐animal co‐culture system (RAC) (e.g., rice‐fish, rice‐duck, and rice‐crayfish) through a global meta‐analysis and identify the potential benefits of global promotion. Compared to traditional monoculture of rice or animal production, the RAC can not only reduce the demand for agricultural land areas, but also increase rice yields (+4%) as well as nitrogen use efficiency of rice (+6%). At the same time, RAC reduces nitrogen losses (−16% runoff and −13% leaching) and methane emissions (−11%), except for rice‐fish coculture systems, which are likely to increase methane emissions (+29%). Furthermore, RAC increases the net income of farmers through reducing cost of fertilizer and pesticide input and achieving higher outputs with more marketable products. According to the development stage of different countries, promotion of RAC will thus realize multiple benefits and aid sustainable intensification. Plain Language Summary: How to feed the growing world population with less pollution is a grand challenge for the 21st century. Rice‐animal co‐culture systems present an ecological integrated farming approach to tackle the challenge. Through a global consensus by synthesizing evidence from existing literature, we found that rice‐animal co‐culture systems could produce more diverse food types and nutrient sources, enhance resource use efficiency and reduce methane emissions, while increasing farmers' income. Global promotion of rice‐animal coculture system has the potential to benefit sustainable development goals. Key Points: Rice‐animal co‐culture systems could produce more diverse food with higher rice yield and extra animal proteinGlobal promotion of rice‐animal co‐culture will reduce nitrogen loss and methane emissions from rice paddiesGlobal promotion of rice‐animal co‐culture will increase income of producers by 152–171 billion US dollars annually [ABSTRACT FROM AUTHOR]

The Chinese government recently proposed ammonia (NH 3) emission reductions (but without a specific national target) as a strategic option to mitigate fine particulate matter (PM 2.5) pollution. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH 3 and acid gas (SO 2 and NO x) emissions. We found that PM 2.5 concentrations decreased from 2000 to 2019, but annual mean PM 2.5 concentrations still exceeded 35 µ g m -3 at 74 % of 1498 monitoring sites during 2015–2019. The concentration of PM 2.5 and its components were significantly higher (16 %–195 %) on hazy days than on non-hazy days. Compared with mean values of other components, this difference was more significant for the secondary inorganic ions SO 42- , NO 3- , and NH 4+ (average increase 98 %). While sulfate concentrations significantly decreased over this period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50 % NH 3 emission reduction for controlling secondary inorganic aerosol (SIA) concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the COVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8 % lower than those in 2017. In addition, the reduction in SIA concentrations in 2017 was greater for 50 % acid gas reductions than for the 50 % NH 3 emission reductions. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by emissions of acid gases, while an additional control of NH 3 emissions would become more important as reductions of SO 2 and NO x emissions progress. [ABSTRACT FROM AUTHOR]

Cropland ammonia (NH3) 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 NH3 emissions, which may be induced by such policies, are not well evaluated. Here, we quantify the China's cropland‐NH3 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‐NH3 emission in China doubled from 1.93 to 4.02 Tg NH3‐N in period 1980–1996, and then decreased to 3.50 Tg NH3‐N in 2017. The prevalence of four agricultural policies may avoid ~3.0 Tg NH3‐N in 2017, mainly located in highly fertilized areas. Optimization of fertilizer management and food consumption could mitigate three‐quarters of NH3 emission in 2050 and lower NH3 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‐NH3 from crop production in China and suggest the need to achieve cropland‐NH3 mitigation while sustaining crop yields in other developing economies. [ABSTRACT FROM AUTHOR]

The Chinese government recently proposed ammonia (NH3) emissions reductions (but without a specific national target) as a strategic option to mitigate PM2.5 pollution. We combined a meta-analysis of nationwide measurements and air quality modelling to identify efficiency gains by striking a balance between controlling NH3 and acid gas (SO2 and NOx) emissions. We found that PM2.5 concentrations decreased from 2000 to 2019, but annual mean PM2.5 concentrations still exceeded 35 µg m-3 at 74% of 1498 monitoring sites in 2015-2019. Secondary inorganic aerosols (SIA) were the dominant contributor to ambient PM2.5 concentrations. While sulfate concentrations significantly decreased over the time period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50% NH3 emission reduction for controlling SIA concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the CoVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8% lower than that in 2017. In addition, the reduction of SIA concentrations in 2017 was greater for 50% acid gas reductions than for the 50% NH3 emissions reduction. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by acid gases emissions, while an additional control on NH3 emissions would become more important as reductions of SO2 and NOx emissions progress. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]