The Steubenville Comprehensive Air Monitoring Program (SCAMP): Associations among fine particulate matter, co-pollutants, and meteorological conditions
The Steubenville Comprehensive Air Monitoring Program (SCAMP): Associations among fine particulate matter, co-pollutants, and meteorological conditions
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DOI：
10.1080/10473289.2005.10464631
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发表时间：
2005-04-01
影响因子：
2.7
通讯作者：
Bilonick, RA
中科院分区：
文献类型：
--
作者：
Connell, DP;Withum, JA;Bilonick, RA
我们测定了2000年5月至2002年5月期间俄亥俄州斯特本维尔的PM2.5及其离子和碳质组分的24小时平均环境浓度。我们还测定了日平均气态共污染物浓度、气象条件以及花粉和霉菌孢子计数。通过线性回归和时间序列模型对数据进行图形分析。细颗粒物(PM2.5)浓度连续数天的升高通常发生在局地高温(特别是夏季)、高压或低风速(特别是冬季)期间，通常随着锋面系统的通过而结束。去除自相关性后，我们观察到PM浓度与CO、NOx和SO2浓度之间存在统计学上显著的正相关。与NO、CO的相关性表现出显著的季节依赖性，秋季和冬季的相关性最强。在具有外部回归变量的时间序列模型中，NOx、CO、SO2、O-3、温度、相对湿度和风速都是PM2.5浓度的显著预测因子，成功地解释了对数转换后的PM2.5日浓度变化的79%。对NOx和温度的系数估计因季节而有很大差异。研究结果为斯特本维尔未来PM2.5减排策略的制定提供了有益的启示。此外，它们还表明，斯特本维尔(和其他地方)的PM流行病学研究需要仔细考虑气态共污染物(如CO和NOx)的潜在混杂影响，以及它们与PM2.5的季节性相关性。
We determined 24-hr average ambient concentrations of PM2.5 and its ionic and carbonaceous components in Steubenville, OH, between May 2000 and May 2002. We also determined daily average gaseous co-pollutant concentrations, meteorological conditions, and pollen and mold spore counts. Data were analyzed graphically and by linear regression and time series models. Multiple-day episodes of elevated fine particulate matter (PM2.5) concentrations often occurred during periods of locally high temperature (especially during summer), high pressure, or low wind speed (especially during winter) and generally ended with the passage of a frontal system. After removing autocorrelation, we observed statistically significant positive associations between concentrations of PM,., and concentrations of CO, NOx, and SO2. Associations with NO, and CO exhibited significant seasonal dependencies, with the strongest correlations during fall and winter. NOx, CO, SO2, O-3, temperature, relative humidity, and wind speed were all significant predictors of PM2.5 concentration in a time-series model with external regressors, which successfully accounted for 79 % of the variance in log-transformed daily PM2.5 concentrations. Coefficient estimates for NOx and temperature varied significantly by season. The results provide insight that may be useful in the development of future PM2.5 reduction strategies for Steubenville. Additionally, they demonstrate the need for PM epidemiology studies in Steubenville (and elsewhere) to carefully consider the potential confounding effects of gaseous co-pollutants, such as CO and NOx, and their seasonally dependent associations with PM2.5.