Baawain Mahad, Al-Mamun Abdullah, Omidvarborna Hamid, Al-Jabri Abdullah
Department of Civil and Architectural Engineering, Sultan Qaboos University, Muscat, Oman.
Oman India Fertilizer Company, Muscat, Oman.
Environ Monit Assess. 2017 Jun;189(6):263. doi: 10.1007/s10661-017-5983-6. Epub 2017 May 10.
Air quality modeling plays an important role in prediction of air pollutants in urban areas. Moreover, it is also an essential component to make crucial decisions in environmental management. In this study, environmental protection agency (EPA) regulatory model (AERMOD) was implemented in order to assess the urban air quality in the city of Muscat, Sultanate of Oman. Dispersion modeling was employed for the prediction of hydrogen sulfide (HS) emissions, a neighborhood claimed issue, from Al-Ansab sewage treatment plant (STP). Meteorological, elevation data, and HS survey results were implemented into the model. From the site survey study, four different HS emission sources were identified as sewage tanker connection points, biofilter, old odor control unit (OCU), and open channels of raw sewage. It was observed that based on maximum 24-h analysis, the ground level concentration outside the STP exceeded the concentration limit, 40 μg/m, recommended by the local regulating agency in Oman. By applying a sensitivity analysis study, the locations with the highest predicted HS levels were identified. The most affected area in the worst-case scenario was the nearby expressway with 450.9 μg/m of HS. The highest ground level concentration of HS was detected in March, while the lowest was measured in December. The model also predicted that the impact of odor nuisance is greater at the summer season than that of other seasons due to the elevated temperatures. The study revealed an adverse environmental impact from the STPs on urban air quality, which may pose a threat to the public health.
空气质量建模在城市地区空气污染物预测中发挥着重要作用。此外,它也是环境管理中做出关键决策的重要组成部分。在本研究中,为评估阿曼苏丹国马斯喀特市的城市空气质量,实施了美国环境保护局(EPA)的监管模型(AERMOD)。采用扩散模型预测了来自安萨卜污水处理厂(STP)的硫化氢(HS)排放,这是一个社区关注的问题。将气象数据、海拔数据和HS调查结果输入该模型。通过现场调查研究,确定了四个不同的HS排放源,分别为污水罐连接点、生物滤池、旧的气味控制单元(OCU)和未经处理的污水明渠。据观察,基于最长24小时的分析,污水处理厂外的地面浓度超过了阿曼当地监管机构建议的浓度限值40μg/m³。通过进行敏感性分析研究,确定了预测HS水平最高的位置。在最坏情况下,受影响最大的区域是附近的高速公路,HS浓度为450.9μg/m³。HS地面浓度最高出现在3月,最低出现在12月。该模型还预测,由于气温升高,夏季气味滋扰的影响比其他季节更大。该研究揭示了污水处理厂对城市空气质量产生的不利环境影响,这可能对公众健康构成威胁。