Air pollution has significant impacts on both the environment and human health. Therefore, urban areas have received ever growing attention, because they not only have the highest concentrations of air pollutants, but they also have the highest human population. In modern societies, urban air quality (UAQ) is routinely evaluated and local authorities provide regular reports to the public about current UAQ levels. Both local and international authorities also recommended that some air pollutant concentrations remain below a certain level, with the aim of reducing emissions and improving the air quality, both in urban areas and on a more regional scale. In some countries, protocols aimed at reducing emissions have come in force as a result of international agreements.

While the routine assessment of UAQ is essential for analysing what has happened in the past, forecasting allows for the prediction of future trends and enables local authorities to plan new strategies aimed at reducing the risk of exposure to high levels of air pollution. For example, the EU directive (2008/50/EC) declared that Member States shall forecast air quality and inform the public if any alert thresholds are likely to be exceeded. However, whilst the forecasting of UAQ and its impact on the environment and human health is of great interest to both policy makers and the public, it is also extremely challenging. Forecasting UAQ requires long-term monitoring of the temporal-spatial variation of air pollutants, as well as data on weather patterns, anthropogenic, and biogenic emissions, and the local- and long-range transport of air pollution.

Three papers in this special issue present work on the development of statistical forecasting models that are superior in terms of their high productivity, but lacking in terms of the physical process. One paper illustrates how, in addition to vehicular traffic, meteorology also plays an important role in UAQ, and it can be used as one of the key predictors in air-quality forecasting models. The approach was based on a generalized additive model and it was applied for nitrogen dioxide () and particulate matter (PM₁₀）在2003年12月至2005年4月的都灵质。另一篇论文介绍了与开发两个经验模型有关的工作：一种预测第二天地面臭氧小时浓度和州空间模型方法的贝叶斯方法。对这些模型的预测进行了评估，这些预测是针对第一种方法优于第二种方法的许多站点。第三篇论文基于多个线性回归模型，对雅典区域的每日最大表面臭氧浓度进行了预测。本文还强调，基本的气象参数非常重要，以预测臭氧浓度水平。此外，一篇论文介绍了塞浦路斯劳动部检查部安装的空气质量管理系统的数据。该系统用于测量NO₂,, CO, Benzene, PM₁₀, and PM_2.5.

原则上，可以将统计模型和论文中提出的空气质量管理系统介绍的统计模型扩展到其他空气质量参数，以开发一个集成系统以预测UAQ。通常，统计模型能够做出高度准确的短期预测，但是它们无法考虑长期影响UAQ的许多化学和物理过程。

The Community Multiscale Air Quality (CMAQ) modeling system and the CB05 mechanism were utilized in Paper IV to investigate the impact of nitrous acid (HONO) chemistry on regional ozone and particulate matter concentrations in the Pearl River Delta region. The results of the model simulations were in good agreement with the observed data for NO_x, SO₂, PM₁₀, and sulfate.

In one paper, the Weather Research and Forecasting model was applied, in conjunction with chemistry packages that were modified for use in the subarctic region, to examine the effects of using low-sulfur fuel in oil-burning facilities on PM_2.5concentrations at breathing level in an Alaska city. The simulation results suggested that introducing low-sulfur fuel would decrease the monthly mean 24 h-averaged concentrations during the winter. The results also suggested that PM_2.5concentrations would further decrease on days with low atmospheric boundary layer heights, a low hydrometeor mixing ratio, low downward shortwave radiation, and low temperatures. Published in this issue, by the same research group and using the same modeling approach, another paper illustrates the effects of exchanging noncertified wood-burning devices with certified ones, on the 24 h-average PM_2.5concentrations in winter. The results showed that changing out 2930 uncertified woodstoves and 90 outdoor wood boilers would reduce the 24 h average PM_2.5concentrations by 6% and result in pollution falling below the alert threshold levels on 7 out of the 55 simulated exceedance days.

Tareq Hussein
Christer Johansson
Lidia Morawska