南京市江宁区2010年气象因素对SO2等大气污染物浓度的影响

目的探讨气象因素对大气污染物浓度的影响,以期建立气象因素与大气污染物浓度关系的模型。方法收集南京市江宁区2010年气象资料(日平均气压、日最高气压、日最低气压、日平均气温、日最高气温、日最低气温、日平均相对湿度、日最小相对湿度、日降水量、日平均风速、日照时数)和大气主要污染物(SO2、NO2、PM2.5)浓度资料,以气象因素对大气污染物浓度进行多元线性回归分析,建立多元回归方程。结果 SO2日平均浓度与日最高气压和日最高气温呈负相关,与最低气压呈正相关;NO2日平均浓度与最低气温呈负相关;PM2.5日平均浓度与日最小相对湿度和日平均风速呈负相关。结论气象因素的变化对于大气污染物浓度有一定影响。在污染物特征及地形地貌基本不变、总的污染物排放相对稳定的情况下,通过建立多元回归方程可以预测气象因素变化对大气污染物浓度的影响。     

深圳市气象因素对SO2等大气污染物的影响研究

目的探讨气象因素对大气污染物的影响及建立气象因素与大气污染物浓度关系的模型。方法收集深圳市2002—2007年气象资料(日平均气压、日最高气压、日最低气压、日气压差、日平均气温、日最高气温、日最低气温、月降雨量、日平均相对湿度、日最小相对湿度、风速)和大气污染物(SO2、NO2、PM10)浓度资料,对大气污染物浓度与气象因素进行多重线性回归分析,建立多元回归方程。结果日最小相对湿度与大气中SO2、NO2浓度呈负相关,日最低气温与大气中NO2浓度呈负相关,日平均相对湿度、风速与大气中PM10浓度成呈负相关,日气压差与大气中PM10浓度呈正相关,SO2、NO2、PM10浓度与各气象因素建立的多元回归方程模型均有统计学意义(P<0.001)。结论气象因素的变化对大气污染物浓度有一定影响,利用气象因素与大气污染物浓度的相互关系可建立反映两者内在关系的多元回归方程模型。     

广州市部分气象因素与大气中SO_2等污染物浓度的关系

为研究广州市2006—2008年大气污染特征,建立气象因素与大气污染物浓度关系的模型,探讨气象因素对大气污染物的影响,收集广州市2006—2008年气象资料(日平均气压、日平均气温、日平均相对湿度、日平均能见度)和大气污染物(SO2、NO2、PM10)资料,对气象因素进行主成分分析,对大气污染物浓度与气象因素进行多重线性回归及主成分回归分析,建立回归方程。结果显示,大气中NO2浓度与月最低气压呈正相关,与月平均能见度呈负相关(P0.001);大气中SO2与月最高气压呈正相关(P0.001),PM10浓度与月最高气压及月最高气温呈正相关(P0.001)。可见气象因素对大气污染物浓度的影响为多因素联合作用。     

深圳市2002～2005年大气污染物浓度与气象因素的关系研究

[目的]探讨大气SO2、NO2、PM10浓度变化与气温、气压、相对湿度的关系。[方法]大气SO2、NO2、PM10浓度和日平均气压、日最大气压、日最小气压、日平均气温、日最高气温、日最低气温、日平均相对湿度、日最小相对湿度的月均值由相应月份的日监测值得出,大气污染物浓度与气象要素的相关关系采用多变量逐步回归分析模型分析。[结果]①大气SO2浓度变化与日最大气压有关,气压的增加有利于SO2浓度的加大,其标化偏回归系数（β）为0.6246;SO2浓度变化与日平均相对湿度有关,湿度的加大有利于SO2浓度的减少（β=-0.7623）。②大气NO2浓度变化与日最大气压有关,气压的增加有利于NO2浓度的加大（β=0.9999）;NO2浓度变化与日最高气温、日平均相对湿度有关,这二者的升高有利于NO2浓度的减少（β分别为-0.4226和-0.6307）。③大气PM10浓度变化与日平均气压有关,气压的增加有利于PM10浓度的加大（β=0.8368）;PM10浓度与日平均相对湿度、日最小相对湿度有关,日平均相对湿度的加大有利于PM10浓度的降低（β=-2.6988）,日最小相对湿度的升高有利于PM10浓度的加大（β=1.7538）。[结论]气温、气压和相对湿度的改变对大气SO2、NO2、PM10浓度有影响。     

基于典型相关分析的潍坊市大气污染物与气象因素关系的初步探讨

为探讨潍坊市大气污染物与气象因素之间的关系,收集该市大气污染物和气象因素监测数据,采用简单相关和典型相关分析探讨二者关系。简单相关分析结果显示,日均气温、日最高气温、日最低气温、气温日较差与大气污染物PM_(2.5)、PM_(10)、CO、NO_2、SO_2相关,其中气温日较差与PM_(2.5)、PM_(10)、CO、NO_2、SO_2呈正相关,日均气温、日最高气温、日最低气温与PM_(2.5)、PM_(10)、CO、NO_2、SO_2呈负相关,均有统计学意义(P0.05);日均相对湿度与PM_(2.5)呈正相关,与PM_(10)、NO_2、SO_2呈负相关;日均风速与PM_(2.5)、PM_(10)、CO、NO_2、SO_2呈负相关,日均降水量与PM_(2.5)、PM_(10)、CO、NO_2、SO_2呈负相关,均有统计学意义(P0.05)。典型相关分析共提取了4对典型相关变量,典型相关系数分别为0.78、0.74、0.48和0.34。提示研究期间潍坊市气温主要影响气态污染物浓度,相对湿度主要影响PM_(2.5)浓度,风速主要对PM_(10)和NO_2浓度产生较大影响,日均降水量和气温日较差主要影响大气颗粒物浓度。     

本溪市大气主要污染物与气象因素相关性

目的分析本溪市2014—2015年大气主要污染物与气象因素的相关性,为大气污染防治提供依据。方法本溪市环境监测站共设立6个大气监测点(溪湖、彩屯、东明、大峪、新立屯和威宁)进行常年大气污染物监测工作。选取2014—2015年大气二氧化硫(SO2)、二氧化氮(NO_2)、可吸入颗粒物(PM_(10))和细颗粒物(PM_(2.5))日均浓度与气象监测资料进行相关性分析和多元逐步回归分析,找出气象因素与大气污染物浓度的关系及气象因素对大气污染物浓度的影响规律。结果 SO_2日均浓度与气温和相对湿度呈负相关(r=–0.793、–0.288,P均0.01);PM_(10)与气温、风速、湿相对度均呈负相关(r=–0.338、–0.176、–0.138,P均0.01);NO_2与温度和风速呈负相关(r=–0.507、–0.313,P均0.01);PM_(2.5)与温度和风速呈负相关(r=–0.379、–0.264,P均0.01)。结论气象因素与大气污染物浓度密切相关,气象因素对大气污染物浓度的影响有一定规律性,可通过回归方程进行模拟预测。     

天津市气象因素对手足口病发病影响研究

目的研究天津市不同气象因素对手足口病发病的影响,为其防控提供理论依据。方法收集天津市2009年至2018年手足口病日发病数据及气象数据(日均气温、日最高气温、日最低气温、日均相对湿度、日降水量、平均气压、平均风速和最大持续风速),利用分布滞后非线性模型分析气象因素与手足口病发病的关系。结果 2009—2018年天津市手足口病共报告发病167 234例,男女性别比为1.5∶1。发病集中在0～10岁,占全部报告发病的97.74%。散居儿童、托幼儿童与学生发病比为8.7∶4.4∶1。手足口病日报告发病数与日均气温、日最高气温、日最低气温、日均相对湿度、日降水量呈正相关,与平均气压、平均风速和最大持续风速呈负相关。日均气温、日均相对湿度和日降水量作为气象因素纳入分布滞后非线性模型。以气象因素中位数为参照,在滞后0 d、日均气温为36℃时,手足口发病风险最高,相对危险度RR(95%CI)值为1.12(1.06～1.18)。日均相对湿度为73%,滞后12 d时手足口发病风险最高,RR值为1.02(1.01～1.03);降水量为130 mm,滞后0 d时手足口病发病风险最高为1.36(0.91～2.02)。结论气象因素对手足口病的影响呈非线性,且存在滞后效应。     

沈阳市某社区医院儿科门诊量与空气质量及气象因素的关系

目的探讨沈阳市某社区医院儿科门诊量与空气质量及气象因素的关系。方法收集2012年1月1日—12月31日沈阳市某医院儿科门诊数据、空气质量指数(AQI)、大气污染级别以及气压、气温等气象监测数据,对上述资料的相关性和滞后效应进行分析,并构建回归方程进行预测。结果 2012年沈阳某医院儿科门诊量与气象指标中的平均气压、平均风速呈正相关,与降水量、平均水气压、平均气温、日最高气温、最低气温、平均相对湿度呈负相关;其中大气污染指数与女童呼吸系统疾病密切相关(P0.01);AQI与当日和滞后1 d的呼吸系统门诊量有相关性(P0.05);多因素回归分析显示呼吸系统门诊量与AQI呈正相关,与平均气压、平均相对湿度、最高气温呈负相关(P0.05)。结论大气污染和气象因素是儿童呼吸系统疾病的重要影响因素。     

基于气象因素的上海市金山区手足口病多元线性回归预测模型

目的应用多元线性回归构建基于气象因素的上海市金山区手足口病预测模型。方法收集上海市金山区2010年至2013年手足口病逐日发病人数与包括日最高气温、日最低气温、日平均气温、日最低相对湿度、日平均相对湿度、日平均气压、日降水量、日平均日照时数、日平均风速在内的9种同期气象资料进行相关分析,并选择相关系数有显著性的气象因素进行手足口病的逐步回归模型构建。结果手足口病发病人数与日最高气温、日最低气温、日平均气温、日平均相对湿度、日最低相对湿度呈正相关性（P<0.05）,与日平均气压、日平均风速呈负相关性（P<0.05）。最终有日平均气压、日平均风速和日最高气温进入模型,回归系数分别为-0.129、-0.299和-0.039,且容忍度与方差膨胀因子均显示模型不存在严重的多重共线性。结论基于气象因素的上海市金山区手足口病预测模型解释性拟合程度较好,可用于短期预测。     

济宁市冬春季大气PM_(2.5)与气象因素相关性研究

目的探讨济宁市2014年1—3月大气PM_(2.5)污染与气象因素的相关性,探讨大气PM_(2.5)浓度变化原因,为大气PM_(2.5)的监测、预警和污染防治提供参考。方法收集济宁市电化厂、火炬城、监测站3个大气自动监测点自2014年1月1日至3月31日的大气PM_(2.5)日均浓度数据,及中国科学数据共享服务网的济宁市地面气象资料数据,并进行相关分析。结果济宁市1月大气PM_(2.5)日均浓度高于2、3月,差异有统计学意义(P0.05),但同时期3个监测点之间的浓度差异无统计学意义(P=0.767)。大气PM_(2.5)日均浓度与相对湿度呈正相关,与能见度、风速呈负相关,其中与能见度的相关性最高。经多元线性逐步回归分析,影响大气PM_(2.5)日均浓度的主要气象因素为能见度、降水量和相对湿度(回归方程:yPM_(2.5)平均浓度=142.658-9.831x能见度-29.436x降水量+0.622x相对湿度,F=37.345,P0.01)。结论气象因素对大气PM_(2.5)有一定影响,其中能见度、降水量和相对湿度对PM_(2.5)日均浓度影响较明显。     

PM(10) exposure, gaseous pollutants, and daily mortality in Inchon, South Korea.

To evaluate the relative importance of various measures of particulate and gaseous air pollution as predictors of daily mortality in Inchon, South Korea, the association between total daily mortality and air pollution was investigated for a 20-month period (January 1995 through August 1996). Poisson regression was used to regress daily death counts on each air pollutant, controlling for time trends, season, and meteorologic influences such as temperature and relative humidity. Regression coefficients of a 5-day moving average of particulate matter less than or = to 10 microm in aerodynamic diameter (PM(10)) on total mortality were positively significant when considered separately and simultaneously with other pollutants in the model. PM(10) remained significant when the models were confined to cardiovascular or respiratory mortality. Sulfur dioxide (SO(2)) and carbon monoxide (CO) were significantly related to respiratory mortality in the single-pollutant model. Ozone exposure was not statistically significant with regard to mortality in the above models, and graphic analysis showed that the relationship was nonlinear. A combined index of PM(10), nitrogen dioxide, SO(2), and CO seemed to better explain the exposure-response relationship with total mortality than an individual air pollutant. Pollutants should be considered together in the risk assessment of air pollution, as opposed to measuring the risk of individual pollutants.     

Association of higher levels of ambient criteria pollutants with impaired cardiac autonomic control: a population-based study

An association between air pollution and increased cardiovascular disease (CVD) mortality has been reported, but underlying mechanisms are unknown. The authors examined short-term associations between ambient pollutants (particulate matter less than 10 microm in aerodynamic diameter (PM10), ozone, carbon monoxide, nitrogen dioxide, and sulfur dioxide) and cardiac autonomic control using data from the fourth cohort examination (1996-1998) of the population-based Atherosclerosis Risk in Communities Study. For each participant, the authors calculated PM10 and gaseous pollutant exposures as 24-hour averages and ozone exposure as an 8-hour average 1 day prior to the randomly allocated examination date. They calculated 5-minute heart rate variability indices and used logarithmically transformed data on high-frequency (0.15-0.40 Hz) and low-frequency (0.04-0.15 Hz) power, standard deviation of normal R-R intervals, and mean heart rate. Linear regression was used to adjust for CVD risk factors and demographic, socioeconomic, and meteorologic variables. Regression coefficients for a one-standard-deviation increase in PM10 (11.5 microg/m3) were -0.06 ms2 (standard error (SE), 0.018), -1.03 ms (SE, 0.31), and 0.32 beats/minute (SE, 0.158) for log-transformed high-frequency power, standard deviation of normal R-R intervals, and heart rate, respectively. Similar results were found for gaseous pollutants. These cross-sectional findings suggest that higher ambient pollutant concentrations are associated with lower cardiac autonomic control, especially among persons with existing CVD, and highlight a putative mechanism through which air pollution is associated with CVD.     

Effects of air pollutants on acute stroke mortality

The relationship between stroke and air pollution has not been adequately studied. We conducted a time-series study to examine the evidence of an association between air pollutants and stroke over 4 years (January 1995-December 1998) in Seoul, Korea. We used a generalized additive model to regress daily stroke death counts for each pollutant, controlling for seasonal and long-term trends and meteorologic influences, such as temperature, relative humidity, and barometric pressure. We observed an estimated increase of 1.5% [95% confidence interval (CI), 1.3-1.8%] and 2.9% (95% CI, 0.3-5.5%) in stroke mortality for each interquartile range increase in particulate matter < 10 microm aerodynamic diameter (PM(10)) and ozone concentrations in the same day. Stroke mortality also increased 3.1% (95% CI, 1.1-5.1%) for nitrogen dioxide, 2.9% (95% CI, 0.8-5.0%) for sulfur dioxide, and 4.1% (95% CI, 1.1-7.2%) for carbon monoxide in a 2-day lag for each interquartile range increase in single-pollutant models. When we examined the associations among PM(10) levels stratified by the level of gaseous pollutants and vice versa, we found that these pollutants are interactive with respect to their effects on the risk of stroke mortality. We also observed that the effects of PM(10) on stroke mortality differ significantly in subgroups by age and sex. We conclude that PM(10) and gaseous pollutants are significant risk factors for acute stroke death and that the elderly and women are more susceptible to the effect of particulate pollutants.     

A time-series study of air pollution, socioeconomic status, and mortality in Vancouver, Canada

We evaluated the relationship between daily levels of particulate and gaseous phase pollutants and mortality within a dynamic cohort of approximately 550,000 individuals whose vital status was ascertained between 1986 and 1999. Time-series methods were applied to evaluate whether there were differential pollutant effects on daily aggregated numbers of deaths in the cohort that was stratified into quintiles of income as defined by the 1991 and 1996 Canadian censuses. The percent change in all-cause, cardiovascular, respiratory, and cancer daily mortality was calculated in relation to short-term changes in levels of a number of particulate (PM(2.5), PM(10-2.5), total suspended particle co-efficient of haze PM(10), SO(4)) and gaseous (O(3), CO, SO(2), NO(2)) pollutants. The estimated effects of air pollution on mortality were adjusted for day of week effects, and several meteorologic variables including temperature, change in barometric pressure, and relative humidity. Several gaseous pollutants were associated with an increased risk of mortality. Specifically for an increase equivalent to the difference between the 90th and 10th percentiles, the estimated percent change in daily mortality based on the 3-day average of NO(2), and SO(2) was 4.0% and 1.3%, respectively. The corresponding changes in mortality associated with SO(2) were much higher when analyses were restricted to death from respiratory disease. Specifically, a difference between the 90th and 10th percentiles was associated with a 5.6% (95% CI= -0.7% to 12.3%). The daily mean coarse fraction (PM(10-2.5)) was associated with increased cardiovascular mortality (estimated change=5.9%, 95% CI=1.1-10.8%). PM(2.5) was not found to be an important predictor of mortality. For NO(2), CO, and SO(2), there was some suggestion of increased risk of all-cause and cardiovascular mortality at lower levels of socioeconomic status. However, these results should be interpreted cautiously due to the small number of deaths observed within each stratum of socioeconomic status.     

如皋地区环境因素对呼吸系统疾病死亡病例发生的影响

目的探讨如皋地区环境因素对当地居民呼吸系统疾病死亡病例发生的影响。方法利用如皋地区2011-2013年居民呼吸系统疾病死亡资料和同期气象数据、大气污染数据,采用冗余分析法分析环境因素与呼吸系统疾病死亡的关系。结果大气污染物中,SO2、NO2、PM10与各类呼吸系统疾病死亡关系密切,O3的影响不确定;气象要素中,温度、气压与其关系密切,而风速、相对湿度的影响不确定。结论环境因素对居民呼吸系统疾病死亡有着重要影响,SO2、NO2、PM10与其呈正相关,其中SO2对肺气肿的影响较其他污染物大;气温与各类呼吸系统疾病死亡人数呈显著负相关,气压则呈显著正相关;春季和冬季主要受各类污染物和气压的影响,春末和夏季主要受温度的影响。此类呼吸系统疾病患者应采取相应措施应对周围环境变化,防止死亡病例的发生。     

Air pollution and ED visits for asthma in Australian children: a case-crossover analysis

OBJECTIVE: We aimed to determine the effects of ambient air pollutants on emergency department (ED) visits for asthma in children. METHODS: We obtained routinely collected ED visit data for asthma (ICD9 493) and air pollution (PM(10), PM(2.5), O(3), NO(2), CO and SO(2)) and meteorological data for metropolitan Sydney for 1997-2001. We used the time stratified case-crossover design and conditional logistic regression to model the association between air pollutants and ED visits for four age-groups (1-4, 5-9, 10-14 and 1-14 years). Estimated relative risks for asthma ED visits were calculated for an exposure corresponding to the inter-quartile range in pollutant level. We included same day average temperature, same day relative humidity, daily temperature range, school holidays and public holidays in all models. RESULTS: Associations between ambient air pollutants and ED visits for asthma in children were most consistent for all six air pollutants in the 1-4 years age-group, for particulates and CO in the 5-9 years age-group and for CO in the 10-14 years age-group. The greatest effects were most consistently observed for lag 0 and effects were greater in the warm months for particulates, O(3) and NO(2). In two pollutant models, effect sizes were generally smaller compared to those derived from single pollutant models. CONCLUSION: We observed the effects of ambient air pollutants on ED attendances for asthma in a city where the ambient concentrations of air pollutants are relatively low.     

气象因素对汉中市城区空气污染的影响

目的探讨气象因素对汉中市城区空气污染的影响。方法以汉中市城区2015年1—12月空气质量监测数据和气象资料为基础,分析温度(T)、露点温度(T_d)、平均海平面大气压(P)等气象因素对空气质量的影响及其空气污染特征。结果 AQI及各污染物浓度可用二次函数很好地拟合,拟合曲线的拐点横坐标出现在6月上旬至7月上旬。相关性分析表明,汉中市城区空气质量主要与PM_(2.5)和PM_(10)浓度有关,且PM_(10)大多由PM_(2.5)贡献;PM_(2.5)浓度受到T、水平大气压(P_0)、P、Td的影响较明显,而受气压趋势(P_a)、湿度(U)的影响较小。T_d对PM_(10)浓度的影响高于PM_(2.5)。对于同一大气污染物而言,P的影响高于P0和Pa。各污染物浓度和气象因素之间存在明显的共线性,PM_(2.5)与其他大气污染物及T、P、T_d所构建的主成分回归模型拟合优度较好且无多重共线性。结论汉中市城区气象因素与空气污染存在一定的关联。     

北京市大气污染与城区居民死亡率关系的时间序列分析

为定量评价北京市大气污染对居民每日疾病死亡率的影响 ,运用时间 -序列分析方法 ,控制了流感、季节等混杂因素的影响后 ,对北京市主要大气污染物CO、SO2 、NOX、TSP、PM10 与居民相应疾病死亡率的相关关系进行了定量评价。以呼吸系统疾病、循环系统疾病、冠心病、慢性阻塞性肺病和消化系统肿瘤疾病死亡人数分别为因变量 ,大气污染物浓度和平均温度、湿度为自变量 ,进行了泊松回归分析。单变量分析结果表明 ,除TSP对冠心病死亡率的影响无显著意义外 ,大气中CO、SO2 、NOX 、TSP浓度与呼吸系统、心脑血管疾病、慢性阻塞性肺病和冠心病死亡率之间的正相关关系均有显著意义 ,而多因素泊松回归得到的暴露 -反应关系模型显示 ,SO2 浓度每提高 10 0 μg m3,呼吸系统、循环系统、冠心病和慢性阻塞性肺病疾病死亡率分别增加 4 2 1%、3 97%、10 68%和 19 2 2 % ;总悬浮颗粒物每增加 10 0 μg m3 ,呼吸系统疾病死亡率增加 3 19% ,循环系统死亡率增加 0 62 %。提示大气污染物浓度的升高会引起相应疾病死亡率的增加