空氣品質數據及污染物影響風險之玫瑰圖

Abstract

一般在進行空氣品質數據及污染源環境影響評估之方向性分析時，經常是以風玫瑰圖(windrose)的盛行風向為分析主要重點，然而空氣污染物擴散、空氣品質惡化及空氣污染源並不完全發生在盛行方向上，若只基於盛行方向分析，可能導致未能適當的分析空氣品質數據之代表性，或監測及影響評估分析均未能掌握真正的主要方向，尤其是風玫瑰圖中未明顯標示的靜風(Calm)部分，往往是容易發生空氣品質惡化或污染物不易擴散與蓄積的氣象條件，本研究基於上述風玫瑰圖在分析工作上之缺失，探討及發展不同的方向性玫瑰圖，以期改善空氣品質數據及污染源環境影響評估之方向性分析。 本研究提出一個濃度玫瑰圖(Concentration-rose)以分析空氣品質數據之方向性分佈，藉由各方向不同濃度區間大小之差異，可以看出污染物的主要方向，並進一步考量靜風蓄積之影響改進濃度玫瑰圖及其他研究所提的時間權重平均污染濃度玫瑰圖(Time-weighted mean concentration rose)。此外，本研究亦提出了一個用於評估單一污染源對週遭環境影響的風險玫瑰圖(risk-rose)，除了分析不同方向之濃度變化外，並依污染物模式模擬濃度、週遭人口密度分佈及損害函數建立風險玫瑰圖。 本研究以桃竹苗空氣品質區內監測站數據及工業區污染源為案例，分別製作各種玫瑰圖，結果顯示部分測站數據所顯示的主要污染方向，並不完全是在風玫瑰圖的盛行方向上，而污染源對週遭環境影響及人口曝露風險，亦發現與風玫瑰圖有明顯的差異，尤其是在考量靜風情形下，其差異更大，相信本研究所提出及修正的濃度及風險玫瑰圖能有效改善以單一風玫瑰圖作為分析主要依據之缺失。

In analyzing the data collected from ambient monitoring stations and environmental impact of a newly established pollution source, directional effects are generally analyzed based on the major direction(s) observed from a wind-rose. However, pollution dispersion phenomena, critical events, and emission sources may not occur in the major direction(s). Furthermore, the Calm portion indicated in a wind-rose is easily ignored, but, for a Calm condition, there exists a high possibility for deteriorating quality or a critical event to occur because its poor dispersive capability. In this study, a modified concentration-rose, a previously proposed time-weighted mean concentration rose, and a time-weighted damage rose were explored and evaluated for their effectiveness in improving the directional analysis for data collected from monitoring stations. These roses were further modified by combining the Calm data with that in the subsequently major direction. Several risk roses were proposed for improving the evaluation of directional environmental impacts of a particular source according to the pollution distribution simulated by ISCST3, population densities in sub-zones adjacent to the source, and a proposed damage function. Data collected from local monitoring stations and a local industrial district were used to implement the case study herein. According to the results obtained, the major pollution directions of some monitored data sets are obviously not consistent with those of corresponding wind-roses. Similar observations can be found for risk roses for a particular source. The modified and proposed roses are expected to improve the directional impact analyses for monitored data and a particular source.