日照市大气质量指数分区预报

利用1999年1月至2002年7月日照市环境监测站监测的污染物浓度资料和探空及本站地面气象资料,分析了日照地区可吸入颗粒物(PM_(10))、二氧化硫(SO_2)、氮氧化物(NO_x)浓度变化的时空分布特征及气象要素的变化对污染物浓度时空分布特征的影响。在此基础上,建立了可吸入颗粒物(PM_(10))、二氧化硫(SO_2)、氮氧化物(NO_x)浓度指数预报方程及大气质量指数分区预报流程。并用VB6.0语言编程在微机上建立了简洁流畅、操作简便的大气质量指数分区预报系统。实际预报结果较好。     

液相色谱法测定环境空气中酞酸酯类

制作了半挥发性有机物中流量采样装置,使用超细玻璃纤维滤膜采样,反相液相色谱法测定环境空气中酞酸酯类,并对样品净化方式、目标化合物在气相和颗粒物上的分布规律及采样器的捕集效率进行了试验.方法在0.50 mg/L～50.0 mg/L之间线性关系良好,当浓缩体积为1.0 mL、采样体积为144 m3时,目标化合物的检出限为0.4×10-3 μg/m3～6.0×10-3 μg/m3;当采样体积为6 m3时,检出限为0.008 μg/m3～0.145 μg/m3.     

环境空气自动监测方法检出限相关问题探讨

探讨了环境空气自动监测中实际评估方法检出限的意义,详细介绍了常规气态污染物自动监测方法检出限的评估方法。并以EC 9850型SO2分析仪为例,说明了环境空气自动监测的测定步骤和方法检出限的计算。     

Modeling of air quality with a modified two-dimensional Eulerian model： A case study in the Pearl River Delta （PRD） region of China

A modified two-dimensional Eulerian air quality model was used to simulate both the gaseous and particulate pollutant concentrations during October 21-24, 2004 in the Pearl River Delta （PRD） region, China. The most significant improvement to the model is the added capability to predict the secondary organic aerosols （SOA） concentrations because of the inclusion of the SOA formation chemistry. The meteorological input data were prepared using the CALMET meteorological model. The concentrations of aerosol-bound species such as NO3^-, NH4^＋, SO4^2-, and SOA were calculated in the fine particle size range （〈2.5 μm）. The results of the two-dimensional model were compared to the measurements at the ground level during the PRD Intensive Monitoring Campaign （IMC）. Overall, there were good agreements between the measured and modeled concentrations of inorganic aerosol components and O3. Both the measured and the modeled results indicated that the maximum hourly O3 concentrations exceeded the China National Air Quality Standard. The predicted 24-h average SOA concentrations were in reasonable agreement with those predicted by the method of minimum OC/EC ratio.     

对导热炉大气污染物排放执行标准的探讨

目前,相关环境标准中均未明确制定关于导热炉大气污染物的排放内容。因此,对于导热炉的大气污染排放,各环境管理及监测部门均没有统一的执行标准。本文从导热炉工作原理、污染物排放特点等方面进行了分析,对其执行标准提出了个人的观点。     

基于智能电网大数据的工业企业大气污染排放特征研究

本文尝试构建基于智能电网大数据的工业企业污染排放预测方法。通过分析上海大中型工业企业用电量与工业总产出、工业总产出与主要污染物直接排放量之间的关联关系,本文建立了工业企业基于用电量的直接污染排放清单估算方法。利用此估算方法,可在实时的智能电网大数据基础上估算工业企业直接污染排放量,服务于大气污染的实时预警和预测。本文研究表明,这种清单估算方法可直接应用于工业企业污染的实时防控,既可服务于政府大气污染监测、应急机制启动时防控对象的选择,也可服务于未来的污染物排放权实时交易市场的供需分析等,是大数据在污染防治领域应用的可行路径。     

海口市臭氧污染特征

基于2013—2015年海口市4个空气质量自动监测站点数据,结合气象资料,分析了海口市O_3的污染特征。结果表明:海口市O_3总体优良,优良天数比例为99.4%,污染天数均为轻度污染;在良和污染天数中,O_3作为首要污染物的天数占40%,超过其他5项污染物占比。海口市10月O_3浓度最高。O_3月均浓度与温度呈负相关关系,同时与风向有密切关系:5—8月气温较高,以南风为主,O_3浓度较低;1月北风频率较高,易受外来污染传输作用,O_3浓度相对较高。O_3超标日以东北风为主,日变化并未呈现单峰型特征,12:00—22:00时段O_3浓度在10%范围内小幅变化。台风外围型和北方冷高压底部型是造成海口市O_3超标的2类典型天气形势。     

室内空气有机污染的研究现状

主要讨论了室内空气中有机物污染的研究现状。重点介绍了室内空气中多环芳烃 (PAHs)、挥发性有机物(VOCs)、醛类化合物等的污染状况及来源。简要叙述了室内空气污染的影响因素及对人体的健康风险评价。     

空气污染视角下北京市产业结构调整的政策模拟研究

空气污染问题是制约经济社会健康发展的重要因素,产业结构调整是缓解该问题的重要途径,探究产业结构调整对于空气污染问题的改善效应具有重要的意义。本文以环境保护和经济增长为双重目标,以投入产出理论为基础,构建了一个一般的具有政策权重的产业结构双目标优化模型。模型目标中的权重体现了政策对两个目标的倾向性需求。给定了某种政策权重,就能根据优化模型计算出最优的产业结构。进一步,我们以SO 2的排放量作为环保指标,以GDP作为经济指标,利用上述模型,依据实际数据,在不同政策权重下,对北京市2017年的产业结构进行了模拟测算,从而给出了与之对应的北京市最优化的产业结构调整方案。特别地,选择了其中三种政策倾向力度,即经济增长偏向性政策、中性政策、环境保护偏向性政策方案,分别给出了最优产业结构方案的数量结果和两个目标的值。我们注意到,2017年的实际值与2016年的实际值相比,2017年的污染物SO 2的排放量大幅减少,且GDP也有所增加,这表明了政府部门的政策相对有效。但是,我们计算出的三种最优化的产业结构对应的两个目标值均优于2017年实际值。事实上,对于经济偏向性政策,最优化的产业结构使得GDP的数量上升更多,而SO 2的排放量也减少了不少;即使是采用环保偏向性政策,不仅使污染物SO 2的排放量更少,而且使GDP的数量仍然高于2017年的实际值。这说明本文提出的通过优化产业结构实现环境保护是一个可行的、合理的途径。     

Residents’ Willingness to Pay for Improving Air Quality in Jinan, China

Along with the progress of urbanization and environ- mental deterioration, residents’ desire for improved air quality is increasing. In order to quantify an individual’s willingness-to-pay (WTP) for improved air quality in Jinan of eastern China, a contingent valuation method (CVM) was employed. A sample of 1,500 residents was chosen on the basis of multistage sampling methods with face-to-face interviews by using a series of hypo-thetical, open-ended scenario questions which were designed to elicit the respondents’ WTP. Results showed that 59.7% of respondents were able to express their WTP and the mean WTP is 100 Chinese Yuan (CNY) per person per year. A probit model on the probability of a positive WTP and a regression model were developed to find the relationship between endogenous variables and WTP. Most parameters in the econometric analysis had the expected sign. Annual household income and expenditure on treating respiratory diseases significantly influence WTP. The rates of positive WTP and the monetary amount are larger for men than for women. Results also showed that people who lived in more polluted areas were willing to pay more for clean air. Unlike developed countries, clean air may only be considered as a public good in China in that more than 40% of respondents had no incen- tive to bear the costs of attempting to achieve better air quality, which indicates the relatively low environmental consciousness.