Large cities in China, including the capital city of Beijing, and their surrounding areas have some of the highest air pollution levels in the world. With over one half of China's population now living in cities, air pollution and air quality are important local and national policy issues. At the same time, China is undergoing changes in health: Deaths in children have come down impressively, and people live to older ages when diseases of the heart and the lung are more common and important. Air pollution in cities is one of the main causes of health problems and disease in China, with especially large effects on the heart and the lung. We know from research in Europe and North America that air pollution adversely affects human health, but we know little about how and why this happens, and whether air pollution from different sources has more or less effects. Even less is known about what these mechanisms are in China, where air pollution may be from different sources and therefore have different chemistry. This knowledge is important for deciding what the most effective strategies to reduce the health effects of air pollution are. In this research project, leading scientists from China and the United Kingdom will work closely to use modern methods in epidemiology and biological sciences to better understand which components of air pollution affects human health in China, and how these effects occur. This knowledge will be used together with information from our related research projects to identify the most effective ways of protecting human health from air pollution in Chinese cities.

In the last few decades China's rising energy requirements have led to increased air pollution emissions from coal-fired power plants. Its motorized transport growth is the fastest in the world with the number of motor vehicles projected to quadruple in the next two decades, reaching over 380 million by 2030. Meanwhile, nearly half of all Chinese still cook and heat their homes with highly polluting biomass and coal fuels. The resulting particulate matter (PM) concentrations in the majority of Chinese cities routinely exceed the World Health Organization's (WHO) annual Air Quality Guideline of 10 microgrammes/m3 by a factor of 10 or more. Epidemiologic studies undertaken in China increasingly confirm links between poor air quality and a range of health risks previously observed in the West. Moreover, they confirm that the number of Chinese that are vulnerable to air pollution is increasing, as evidenced by a large and growing burden of disease from chronic non-communicable diseases - such as ischemic heart disease (IHD), cerebrovascular disease, chronic obstructive pulmonary disease (COPD), and cancer. Research to enhance the understanding of the impact of environmental exposures on human health is needed to influence both government policy on pollution and also individual behaviours. The outcomes of the research described in this proposal will extend our understanding of the impact of air pollution on human health to a megacity in the world's largest country and promote evidence-based policies that in turn may greatly improve the health and quality of life of China's ageing population - both of which are important sustainable development aims. Working closely with Chinese scientists we will recruit a panel of 240 subjects from urban and peri-urban Beijing. Subjects will be recruited from two existing populations cohorts (PRC-USA and INTERMAP) ensuring a rich source of baseline data and stored samples for access. Across the project period we will obtain detailed information on the current health status of the subjects, details of the personal exposure to air pollution and biosamples for biomarker analysis. The UK has been at the heart of the scientific study of air pollution issues over many decades, whereas such scientific studies are much newer in China. Although the Chinese teams have developed a high level of expertise in some areas, the UK team will provide strong complementary expertise, in particular in personal exposure air pollution measurements and biomarker analysis. Inherent throughout however is the synergistic combination of Chinese expertise and capability, complementary UK air quality instrumentation and health expertise. Therefore, this project will serve as a new platform to further enhance the research capacity of the Chinese teams in air pollution and its impact on health, which will leave a legacy beyond the project lifetime, thus contributing to the continuous improvement of life and welfare of more than a billion people.

The aftermath of explosive volcanism is ecologically important in Indonesia but difficult to study because of its unpredictability. In this proposal, we propose to monitor ecosystem recovery after volcanic eruptions with a specific focus on soil micro-organisms and how they can mediate initial soil development in fresh ash deposits. Whilst previous studies have examined microbial communities in 'young' volcanic environments, the age of these deposits was generally in the order of years, thereby missing the key earliest stages of succession during which microbes start to modify the initial edaphic environment. Major volcanic activity at Anak Krakatau, an iconic island volcano in Indonesia, in December 2018 led to a complete reconfiguration of the island and the rare opportunity to study microbial recolonisation and the importance of microbes in ecosystem recovery. In this urgency project, we will sample ash/soils from Anak Krakatau within a few months of the eruption producing a novel dataset. Microbial diversity will be compared with that in the spore-rain to assess if there are constraints to microbial colonisation. We will also set up a series of experiments whereby we inoculate ash/soil to determine how the colonisation of microbes can influence carbon and nutrient accumulation in the ash substrate and the growth of pioneer plant species, and conversely how constraints to colonisation might impede it. Understanding the development of soils over volcanic ash is important because they are very fertile and support high population densities as well as sequestering large amounts of carbon over decadal timescales.

China has only 10% of the world arable land and water resources, but has to feed 20% of the world population. Moreover, the population continues to increase, while the amount of arable land is shrinking due to pollution, urban sprawl, groundwater depletion, and other stresses. With future climate change expected to only worsen these pressures, the accurate monitoring of agricultural productivity is essential to China's future food security, in addition to the economic development of low-income rural regions. In no part of the country is this more essential than China's north plain. This has historically been the breadbasket of China. Today, however, it faces an exceptionally challenging combination of very high population densities and ecological stresses, and low levels of household income. Traditionally, researchers have used two general methods for monitoring agricultural productivity. The first, which has long been used by Chinese government agencies, is to combine field surveys of crop growth, with mathematical models of crop growth processes, to construct estimates of changing harvest yields over time. The second, which has risen to prominence more recently, is to use satellite imagery to continuously assess agricultural productivity. Each of these techniques has its own notable strengths and weaknesses. Survey-calibrated models of crop growth are able to produce highly accurate estimates of yields in the limited areas where survey data has been collected; however, their accuracy drops off significantly outside of these areas. On the other hand, satellite remote sensing data offers universal geographic coverage; however, the resolution of this data is extremely coarse over either time or space. MODIS data, for example, provides near-daily data that can be used to assess the productivity of every single farm in China. However, the spatial resolution of pixels is only 500-1000 meters, an area which will invariably be contaminated, in densely populated China, by a mixture of roads, villages, and other non-agricultural land uses in addition to the farmland actually being studied. Other satellites (e.g. LandSat TM and forthcoming Sentinel) provide finer scale pixel resolution than MODIS; however, they do not cover the same sites as often, making it harder to smoothly track agricultural production over time. Reflecting the wider explosion of the field of "big data" analysis, rapid strides have been made recent years in the development of so-called "data assimilation" techniques. These can be broadly described as statistical methodologies that allow for otherwise incompatible datasets to be combined together, in order to produce hybrid datasets that are superior to any of their predecessors. The basic objective of the proposed project is to apply advanced data assimilation techniques to multiple types of crop data-from both survey-calibrated crop growth models and satellite imagery-to produce superior estimates of Chinese agricultural productivity than would be possible using any of these data sources by itself. In addition to making use of more advanced statistical methods than previous studies, this analysis will be among the first to make use of data from the forthcoming Sentinel and the Chinese GF satellites. Taken together, we expect that the result will be the most accurate portrait created to date of changing agricultural production in the North China Plain. Moreover, having created this data, we will be able to apply it predictively in conjunction with modelled scenarios of future climate change, in order to map and assess the likely geographies of agricultural stress that this will create. Ultimately, the findings of this project will directly inform work by academic researchers, national and regional Chinese governmental authorities, agritech companies in both China and the UK, and extension workers directly advising farmers in China.

Over the past few months, we have laid the groundwork for the ReproHum project (summarised in the 'pre-project' column in the Work Plan document) with (i) a study of 20 years of human evaluation in NLG which reviewed and labelled 171 papers in detail, (ii) the development of a classification system for NLP evaluations, (iii) a proposal for a shared task for reproducibility of human evaluation in NLG, and (iv) a proposal for a workshop on human evaluation in NLP. We have built an international network of 20 research teams currently working on human evaluation who will actively contribute to this project (see Track Record section), making combined contributions in kind of over £80,000. This pre-project activity has created an advantageous starting position for the proposed work, and means we can 'hit the ground running' with the scientifically interesting core of the work. In this foundational project, our key goals are the development of a methodological framework for testing the reproducibility of human evaluations in NLP, and of a multi-lab paradigm for carrying out such tests in practice, carrying out the first study of this kind in NLP. We will (i) systematically diagnose the extent of the human evaluation reproducibility problem in NLP and survey related current work to address it (WP1); (ii) develop the theoretical and methodological underpinnings for reproducibility testing in NLP (WP2); (iii) test the suitability of the shared-task paradigm (uniformly popular across NLP fields) for reproducibility testing (WP3); (iv) create a design for multi-test reproducibility studies, and run the ReproHum study, an international large-scale multi-lab effort conducting 50+ individual, coordinated reproduction attempts on human evaluations in NLP from the past 10 years (WP4); and (v) nurture and build international consensus regarding how to address the reproducibility crisis, via technical meetings and growing our international network of researchers (WP5).