Fundación Centro de Estudios Ambientales del Mediterráneo, Valencia, Spain.
J Environ Manage. 2010 Jan-Feb;91(3):662-76. doi: 10.1016/j.jenvman.2009.09.030. Epub 2009 Oct 22.
The characterization and evaluation of the impact that an industry is likely to have on the surrounding ozone levels is one of many problems confronting air quality managers and should be taken into consideration when authorizing its installation. The correct management of an environment, in terms of monitoring existing industries and planning new activities, requires adequate knowledge of the processes sustained by the industrial emissions therein. This paper explores the improvements in air quality management arising from taking into account the uncertainties involved in the photochemical modeling of the impact of an industry on surface ozone levels. For this, we evaluate the impact on ozone levels of a power plant located in an industrial area of southwestern Spain (Huelva). The evaluation takes into account the effects of both emissions' uncertainty and the non-linear chemistry between ozone and its precursors, thus providing a probable range of increase over the normative values (hourly and 8-hourly maximums) defined in the European Directive. The proposed methodology is easily applicable by air quality managers. Advanced modeling techniques were used for the power plant assessment, MM5 atmospheric modeling system, and air quality model CAMx. The results from meteorology and ozone forecasts have shown acceptable agreement with the observations. The spatial distribution of the impact is found to be strongly determined by mesoscale meteorological processes, which are reinforced by the local orography; there is also a marked temporal evolution. The industrial plume is observed to induce a decrease (or maintenance) of the ozone levels near the emission source (0-10km), and an increase in the ozone concentrations farther away (with maximums between 10 and 50km). In fact, in the meteorological episodes with a predominance of local breeze circulations, impacts have been detected at distances of more than 100km from the emission source. Sensitivity of the power plant impact to variations in ozone precursor emissions is described, and the scenarios and the points in the domain presenting higher sensitivity and registering larger impacts are also identified. The results show that the largest impacts take place in emission scenarios where the NO(x) has been reduced with respect to the base case scenario. In contrast, in scenarios where the VOC emissions are reduced with respect to the base case scenario, the impact is smaller or remains unchanged. This is important in areas like the study case, where there is a high percentage of biogenic VOC emissions and the industrial areas are close to natural protected areas and agricultural fields.
对工业可能对周围臭氧水平产生的影响进行描述和评估是空气质量管理者面临的众多问题之一，在授权其安装时应将其考虑在内。从监测现有工业和规划新活动的角度来看，正确管理环境需要对工业排放物所维持的过程有足够的了解。本文探讨了在考虑工业对地面臭氧水平影响的光化学建模中涉及的不确定性的情况下，空气质量管理得到的改进。为此，我们评估了位于西班牙西南部（韦尔瓦）一个工业区的发电厂对臭氧水平的影响。评估考虑了排放不确定性和臭氧与其前体之间的非线性化学的影响，从而提供了超出欧洲指令中定义的规范值（每小时和 8 小时最大值）的可能增加范围。所提出的方法易于被空气质量管理者应用。先进的建模技术用于评估发电厂，即 MM5 大气建模系统和空气质量模型 CAMx。气象和臭氧预测的结果表明与观测结果具有良好的一致性。影响的空间分布强烈取决于中尺度气象过程，这些过程受到局部地形的加强；还存在明显的时间演变。观察到工业羽流在排放源附近（0-10km）导致臭氧水平降低（或维持），而在更远的地方（10-50km 之间有最大值）臭氧浓度增加。实际上，在以地方性微风环流为主导的气象事件中，在距离排放源 100km 以上的地方已经检测到了影响。描述了发电厂影响对臭氧前体排放变化的敏感性，并确定了具有较高敏感性和较大影响的场景和区域内的点。结果表明，在相对于基准情况减少了 NO(x)的排放情景下，影响最大。相比之下，在相对于基准情况减少了 VOC 排放的情景下，影响较小或保持不变。在研究案例中，这种情况很重要，因为该地区的生物源 VOC 排放量较高，工业区靠近自然保护区和农田。
