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1.
J. B. Harcum Jim C. Loftis Robert C. Ward 《Journal of the American Water Resources Association》1992,28(3):469-478
ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily. 相似文献
2.
Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations
to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the
effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to
the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other
hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the
time series analysed, due to their strong masking effects.
Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations
observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic
density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and
climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February
2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied.
One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong
persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons
is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological
variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial
dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter.
The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O3 and PM to examine underlying trends.
Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model
yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval
for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in
trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates
out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results
in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal
variations.
Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the
analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological
conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions.
There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle
and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic
density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions
which is a direct consequence of the holiday period.
Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend
results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect
of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering
the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an
estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions.
Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant
reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site
with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes
in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability 相似文献
3.
G. D. Kataev 《Russian Journal of Ecology》2005,36(6):421-426
The effect of industrial air pollution on natural small mammal populations has been studied in the northern taiga subzone of the boreal forest zone. The results of long-term monitoring have been used to demonstrate the possibility of predicting changes in the main population and community characteristics of the animal species studied as dependent on the degree of anthropogenic impact. 相似文献
4.
采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统(PEMS)实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据. 相似文献
5.
基于船舶自动识别系统(Automatic Identification System,AIS)数据表征船舶排放是目前船舶排放空间表征的主流方法,但AIS船舶轨迹点缺失会造成船舶排放量低估和船舶空间分布表征错误,进而影响船舶排放控制区的划分.为改进船舶排放空间表征,本研究以2013年广东省AIS船舶数据为例,采用基于时间和经纬度的三次样条方法对AIS船舶轨迹进行修复,结合动力法计算船舶排放,分析对比AIS轨迹修复前后船舶排放表征的差异,并利用空气质量模型和卫星观测评估AIS轨迹修复对船舶排放表征和广东沿海空气质量模拟的改进效果.结果表明:轨迹修复后广东省海域船舶轨迹点总数由4685773个增至5746664个,船舶NOx排放量增加了0.6%.对于轨迹点与排放缺失集中的粤东海域,轨迹修复后船舶轨迹点数增加了88%,NOx排放量在广东省船舶排放量的占比提升至22%,特别是在粤东重点修复海域NOx排放量增加了2.7倍.原始轨迹在广东省海域较为稀疏,在粤东海域有明显轨迹缺失;轨迹修复后广东省海域船舶轨迹更为密集,粤东海域船舶轨迹得以补充,船舶排放空间分布更连贯.对比模拟结果与卫星观测结果,轨迹修复后粤东重点修复海域船舶模拟浓度与观测浓度的偏差由51%减至6%,总体上船舶排放模拟结果更接近卫星观测结果. 相似文献
6.
船舶排放是我国沿海地区重要的人为排放源,但现有的船舶排放评估研究大多只关注区域尺度的影响分析,而且忽视了排放清单的不确定性,这在一定程度上削弱了评估结果的可靠性.为此,本文利用WRF-SMOKE-CAMQ空气质量模型,定量评估了船舶排放及其不确定性对我国七大沿海港口城市夏季空气质量的影响,结果表明:船舶排放对我国主要沿海港口城市的SO2、NOx和PM2.5浓度贡献范围分别为16.5%~62.5%、21.9%~72.9%和5.9%~26.0%,尤其对宁波、青岛和深圳等港口城市空气质量的影响显著,主要是由于港口较高的船舶排放以及气象传输两方面原因造成的;如果考虑船舶排放清单的总量不确定性,船舶排放对沿海港口城市夏季SO2、NOx和PM2.5的影响分别呈现1.0~3.1,2.1~5.5,0.3~0.9μg/m3的波动;考虑船舶排放清单的时空分配不确定性,船舶排放对沿海港口城市夏季SO2、NOx和PM2.5的影响分别呈现1.9~15.7,5.1~29.3,0.6~2.5μg/m3的波动.可见,船舶排放清单的不确定性对沿海城市船舶排放贡献影响量化有明显的影响.所以在评估船舶排放对港口城市空气质量的影响时,要考虑船舶排放清单的不确定性,尤其是时空分配的不确定性.而合理的时空分配能够提高船舶排放清单的质量和对沿海空气质量模拟的准确性. 相似文献
7.
为分析生物气溶胶释放对人群潜在影响风险的情况,利用CALPUFF模型定量模拟了2019年7月24~8月20日中牧兰州生物药厂含菌气溶胶扩散、浓度空间分布、对人群潜在健康风险,并结合公开报道的检测数据开展验证.结果显示:生物药厂的含菌气溶胶排放源附近高值区主要集中于厂区四周,影响范围主要以厂区为中心,并向四周逐渐扩散;检测结果中兰州兽研所1#,兰州大学2#地区健康风险比例41.49:1,在模拟的相对风险大小的误差区间(36.15±8.48)范围内,说明本研究含菌气溶胶对人群潜在影响风险的模拟结果可信. 相似文献
8.
秸秆还田是有效利用资源、增加土壤有机质含量和培肥地力的有效措施,但也会影响土壤NH3挥发和N2O的排放.探索不同秸秆还田方式对NH3挥发和N2O排放的影响对于减少土壤氮素损失和保护生态环境具有重要意义.采用田间小区试验,利用Los Gatos Research(LGR)超便携NH3分析仪和密闭式静态箱-气相色谱法探究不同秸秆还田方式下土壤NH3挥发和N2O排放的特征,试验设4个处理(覆盖还田,即表面覆盖玉米秸秆,0~20和20~40 cm土壤分层扰动后填回,记为JG0-0;常规还田,即秸秆与0~20 cm土壤混合,20~40 cm土壤扰动后填回,记为JG0-20;深还田,秸秆与20~40 cm土壤混合,0~20 cm土壤挖出后填回,记为JG20-40;对照处理,即无玉米秸秆还田,0~20和20~40 cm土壤分层扰动后填回,记为CK).结果表明:①相比于CK,不同秸秆还田方式均显著降低了土壤NH3挥发量,增加了土壤N2O排放量.与CK相比,JG0-0、JG0-20和JG20-40处理下土壤NH3累积排放量分别减少了12.38%、9.87%和5.73%;土壤N2O累积排放量分别增加了30.19%、82.82%和36.53%,其中JG0-0和JG20-40处理之间无显著性差异.②JG20-40处理下玉米产量显著高于其他处理,比CK增加了23.15%,JG0-0处理下玉米产量高于CK和JG0-20处理,但并未达到显著水平.③对于NH3和N2O这两种气体的总累积排放量,各处理间均达到显著性差异.与CK相比,JG0-0、JG0-20和JG20-40处理下NH3和N2O总累积排放量分别增加了16.67%、52.08%和22.92%.④不同秸秆还田方式下的氮素气态损失率均高于CK,JG0-0、JG0-20和JG20-40处理下氮素气态损失率分别比CK增加了17.50%、52.50%和22.50%.因此,综合考虑土壤NH3挥发量、N2O排放量和玉米产量等因素,JG0-0处理优于JG20-40、JG0-20处理. 相似文献
9.
京津冀及周边地区水泥工业大气污染控制分析 总被引:1,自引:0,他引:1
以京津冀及周边地区水泥工业为研究对象,基于产排污系数法,建立了水泥工业主要大气污染物排放计算方法,对2016年该地区水泥工业主要大气污染物排放控制水平进行了分析.结果表明:京津冀及周边地区2016年水泥工业SO2、NOx、PM(有组织)排放量分别达到3.2×104t、23.9×104t、9.7×104t,较2015年分别减少24.1%、18.2%、27.2%,各项污染物大幅下降.水泥工业PM无组织排放量占PM总排放量的45.4%,仍需要采取集中收集的方式加强治理.山东、河南是水泥工业SO2、NOx、PM、PM10、PM2.5重点排放来源,应通过化解过剩产能降低污染排放.从各工艺来看,新型干法工艺应考虑采用高效脱氮脱硫技术、协同处置技术、高效大型袋式除尘技术等新技术,进一步降低各项污染物的排放量;粉磨站也需进一步提高污染治理水平. 相似文献
10.