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。虽然影响健康的确切生物学途径和机制仍有待确定，但有充分证据表明，暴露在室外空气污染中可能会损失数月至数年的预期寿命。这些负面影响目前在世界上最大的城市和快速发展的经济体中经历的人不成比例地受到影响。空气污染的基本原因已被理解；用于电力、交通、烹饪和取暖的化石燃料的燃烧、农业排放、资源开采和粉尘等等，都起到了一定作用。在过去的两个世纪里，经济扩张始终与空气污染加剧以及负面的社会和健康后果的过渡期密切相关。21世纪的一个关键的全球挑战是创建一个框架--科学、监管和技术--使经济发展能够提高个人的繁荣和生活质量，而不会损害空气污染的副作用。然而，与空气污染相关的许多过程本质上是非线性的，空气的极其复杂的组成，无论是气体还是颗粒，都很难确定直接的因果关系。污染物经常以意想不到的方式相互作用，可能会从表面上合理的政策干预中产生负面的意外后果。这是一个关键领域，科学上的理解仍然不完整。无法完全描述城市大气的化学和物理特性，限制了社会创造有效的、不与更广泛的发展和经济目标相冲突的解决办法的能力。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，城市以外的偏远排放如何影响城市人口，以及污染本身可能如何影响对城市气象的反馈和改变。该项目重点研究有害空气污染的三种关键类型：颗粒物(简称PM)、二氧化氮(NO2)和臭氧。该项目是由十所英国大学、三家中国领先的研究机构、中国科学院、北京大学和三家英国合作研究机构(CERC、NPL、Met Office)合作完成的。该项目的中心是在北京市中心进行的两个密集观测时期，冬季和夏季的大气条件截然不同。这些实验将使用一座独特的1000英尺高的气象塔在表面和垂直方向进行测量。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。该项目将使用英国和中国的最先进模型，并开发方法来生成非常高空间分辨率的地表污染估计，这类数据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是必不可少的。

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.