An Integrated Study of AIR Pollution PROcesses in Beijing (AIRPRO)

众所周知，空气污染对人类福祉、植被和一般生活质量具有重大负面影响。虽然对健康影响的确切生物途径和机制仍有待确定，但有充分的证据表明，暴露于室外空气污染可能会导致数月至多年的预期寿命损失。目前，生活在世界最大城市和迅速发展的经济体中的人们不成比例地经历着这些负面影响，人们了解空气污染的基本原因;电力、运输、烹饪和取暖燃烧化石燃料、农业排放、资源开采、灰尘等都是造成空气污染的原因。在过去的两个世纪里，经济扩张一直与空气污染加剧以及负面社会和健康后果的过渡时期密切相关。21世纪世纪全球面临的一个关键挑战是建立一个科学、监管和技术框架，使经济发展、个人繁荣和生活质量的提高，而不损害空气污染作为副作用。许多与空气污染相关的过程本质上是非线性的，空气的组成非常复杂，既有气体，也有颗粒，很难建立直接的因果关系污染物往往以意想不到的方式相互作用，表面上合理的政策干预可能产生意想不到的负面后果。这是一个科学认识仍然不完整的关键领域。无法充分描述城市大气的化学和物理性质，限制了社会创造有效解决方案的能力，这些解决方案既可行，又不与更广泛的发展和经济目标相冲突。该项目解决了城市空气过程中仍然存在的一些关键不确定性，包括污染化学物质如何在大气中转化或氧化，气体和颗粒如何相互作用，污染如何通过天气分散，来自城市以外的远程排放如何影响城市人口，以及污染本身的存在如何影响反馈和改变城市气象。该项目重点研究三种主要类型的有害空气污染：颗粒物（简称PM），二氧化氮（NO2）和臭氧O3。该项目由10所英国大学、3所中国领先的研究机构、中国科学院、北京大学和3个英国合作研究机构（CERC、NPL、Met Office）合作完成。该项目的核心是在北京市中心进行两个时期的密集观测，冬季和夏季的大气条件截然不同。实验将在表面进行测量，并使用独特的1000英尺气象塔进行垂直测量。这些实验将产生一个复杂的多参数数据集，可以挑战最先进的城市污染计算机模型。通过用详细的数据挑战模型，可以评估它们的能力，识别它们的弱点和失败，然后有针对性地进行改进。这一点至关重要，因为实现更好空气质量的途径是通过以科学理解为基础的政策，而在空气污染科学中，这种理解被封装在这些计算机模型中。该项目将使用来自英国和中国的最先进的模型，并开发方法来生成对地表污染的非常高的空间分辨率估计，这是一种在研究污染对健康的影响或评估未来政策可能有多成功时必不可少的数据。

Air pollution is well established as having major negative impacts on human well-being, vegetation and general quality of life. Whilst the exact biological pathways and mechanisms for health impacts remain to be established, there is ample evidence to demonstrate that months to many years of life expectancy can be lost through exposure to air pollution outside. Those negative impacts are currently disproportionately experienced by those in living the world's largest cities and in rapidly developing economies.The basic causes of air pollution are understood; the combustion of fossil fuels for electricity, transport, cooking and heating, emissions from agriculture, from resource extraction, dust and so on, all play a part. Over the past two centuries economic expansion has always been closely tied to transition periods of increased air pollution and negative social and health outcomes. A key global challenge for the 21st century is to create a framework - scientific, regulatory, and technological - which enables economic development, with increases in individual prosperity and quality of life, without damaging air pollution as a side effect.Many of the processes associated with air pollution are non-linear in nature however, and the extremely complex composition of air, as both gases and particles, can make it very difficult to establish direct cause-and-effect. Pollutants often interact with one another in unexpected ways that can create negative unintended consequences from superficially reasonable policy interventions. This is a key area where scientific understanding remains incomplete. The inability to fully describe the chemistry and physics of the urban atmosphere limits society's ability to create effective solutions that work, and that do not conflict with wider developmental and economic goals. This project tackles some of the key uncertainties that remain in urban air processes, including how polluting chemicals are transformed or oxidised in the atmosphere, how gases and particles interact, how pollution is dispersed by weather, how remote emissions from outside the city impacts on urban populations and how the presence of pollution itself may affect feedback and alter on meteorology in cities. The project focuses its study on three key types of harmful air pollution: particulate matter (referred to as PM), nitrogen dioxide (NO2), and ozone O3. The project is a collaboration between ten UK Universities, three leading Chinese research institutes, all part of the Chinese Academy of Sciences, Peking University and three UK partner research organisations (CERC, NPL, Met Office). The project centre-piece are two periods of intensive observations in the centre of Beijing, in the contrasting atmospheric conditions of winter and summer. The experiments will make measurements at the surface, and in the vertical using a unique 1000ft meteorological tower. These experiments will generate a complex and multiparameter dataset that can challenge state of the art computer models of urban pollution. By challenging models with detailed data, their capabilities can be assessed and their weaknesses and failings identified, and then targeted for improvement. This is vital since the pathway to achieving better air quality is through policy that is underpinned by scientific understanding, and in air pollution science, that understanding is encapsulated in these computer models. The project will use state of the art models from the UK and from China, and develop methods to generate very high spatial resolution estimates of pollution at the surface, a type of data that is essential when studying the health effects of pollution, or evaluating how successful a future policy might be.