Environmental forensic investigation of the air pollution from a cement manufacturing unit

Abstract

Cement manufacturing is a process that results in the emission of significant quantities of suspended particulate matter (SPM) to the ambient air. An environmental forensic investigation was carried out in the surroundings of a major cement manufacturing unit at a place called Coimbatore in the southern Indian state of Tamil Nadu. The investigation was carried out to identify the contribution of the cement manufacturing unit to the SPM concentration of the surrounding air environment. The sampling points’ selection and sample collection were done following the principles outlined in the INTERPOL Manual for Pollution Crime Forensic Investigation. On-site monitoring of the air samples was carried out using Mini Laser Aerosol Spectrometer (GRIMM, Mini-LAS Model 11R). The instrument was capable of measuring particles ranging from 0.25 to 32 µm and classifying them into 31 size channels. The test results at majority of the monitoring locations were well above the limits specified in the National Ambient Air Quality Standards of India. Microscopic studies of the dust samples were carried out for surface texture and particle shape. The spatial distribution of particles was analysed using geographic information system (GIS) for the visual identification of the extent of the pollution by keeping the cement factory as the focal point. The results from the GIS and microscopic analysis established the role of the cement factory in the particulate matter pollution of its surroundings, specifically in the areas North-West of the factory. The successfully adopted procedure can serve as a guideline for the environmental forensic investigation of similar pollution incidences.     

海洋颗粒有机碳的遥感探测与应用分析

海洋颗粒有机碳(POC)监测对研究海洋碳循环和全球变化有重要意义。为寻求POC探测的有效方法,先讨论了POC的定义组成,介绍了POC的常规测定方法及国内外POC相关研究进展,接着介绍了国外POC遥感探测方法原理。通过对常规测定方法和遥感探测方法优缺点对比分析,我们认为遥感探测海洋POC方法将成为海洋环境监测的重要手段。采用2009年8月的MODIS数据,借鉴蓝绿光比值法建立的POC遥感反演模型,进行了渤海POC的遥感探测,从大尺度揭示了整个渤海POC的分布态势,最高值达370 mg/m3。结果表明:POC遥感探测方法可有效、迅捷、直观反映海区POC变化,因此研究建立具有区域特点的POC生物光学遥感模型用于POC监测,将是海洋环境监测和海洋碳循环研究的重要方向之一。     

可吸入颗粒物污染与气象因子的关系

对闸北区空气自动监测站2009年SO2、NO2、PM10的浓度和气象参数变化特征进行研究,可吸入颗粒物的时间变化特征表明,总体上呈现冬春季高、夏秋季低;PM10与降水量、相对湿度、温度呈现一定的负相关性,但与风速的相关性随季节不同而不同,与气压略呈正相关性。对典型日和灰霾日PM10、SO2、NO2以及相应气象因子的特征进行了分析比较。     

呼和浩特市工业料堆扬尘排放清单研究

颗粒物污染是影响中国城市空气质量的首要因素。工业料堆扬尘是城市大气颗粒物污染的主要来源之一。本文通过对呼和浩特市建成区内典型行业风蚀、作业及交通运输扬尘进行采样分析,应用美国AP-42提供的模型,以2006年作为基准年,建立了呼和浩特市工业料堆排放清单。研究结果表明:呼和浩特市建成区内工业料堆扬尘排放量为TSP:5 305 t/a,PM10:1 012 t/a,PM2.5:267 t/a。从空间分布看玉泉区工业料堆扬尘排放量最大,其次是赛罕区。行业分布上排放最大的行业是建材工业,其次是电力热力工业,最少的是化工工业。在各行业类别的工业料堆排放量中,交通运输扬尘排放量是最大的。     

城市大气颗粒物背景值涵义及定值方法

城市大气颗粒物背景值的概念对防治城市大气颗粒物污染具有重要意义。城市大气颗粒物背景值不同于颗粒物本底值。本底值是指不受人类活动影响的自然条件下颗粒物的浓度值,而背景值是个相对值,其所在的环境条件有可能已经受到了环境污染。影响城市大气颗粒物背景值的因素主要包括两个方面:一是污染源,主要包括城市本地源排放和外来颗粒物,二是颗粒物扩散的天气和气象因素。将城市大气颗粒物的背景值定义为在一定时期内,由于城市本身的排放,城市大气环境中颗粒物的浓度水平。通过分析总结近年来人们对大气颗粒物垂直分布规律的研究,探讨了采用监测一定高度处大气颗粒物,结合气象因素确定城市环境空气中大气颗粒物背景值的方法。     

Measurement of air exchange rates in different indoor environments using continuous CO2 sensors

A new air exchange rate (AER) monitoring method using continuous CO₂ sensors was developed and validated through both laboratory experiments and field studies. Controlled laboratory simulation tests were conducted in a 1-m³ environmental chamber at different AERs (0.1-10.0 hr^-1). AERs were determined using the decay method based on box model assumptions. Field tests were conducted in classrooms, dormitories, meeting rooms and apartments during 2-5 weekdays using CO₂ sensors coupled with data loggers. Indoor temperature, relative humidity (RH), and CO₂ concentrations were continuously monitored while outdoor parameters combined with on-site climate conditions were recorded. Statistical results indicated that good laboratory performance was achieved: duplicate precision was within 10%, and the measured AERs were 90%-120% of the real AERs. Average AERs were 1.22, 1.37, 1.10, 1.91 and 0.73 hr^-1 in dormitories, air-conditioned classrooms, classrooms with an air circulation cooling system, reading rooms, and meeting rooms, respectively. In an elderly particulate matter exposure study, all the homes had AER values ranging from 0.29 to 3.46 hr??1 in fall, and 0.12 to 1.39 hr^-1 in winter with a median AER of 1.15.     

An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.     

Air quality management in China: Issues, challenges, and options

This article analyzed the control progress and current status of air quality,identified the major air pollution issues and challenges in future,proposed the long-term air pollution control targets,and ...     

Improved source assessment of Si, Al and related mineral components to PM10 based on a daily sampling procedure

Samples obtained from an industrialized valley in the East Alpine region were collected daily for a half year and analyzed using X-ray fluorescence to examine the elements Si,Al,Fe,Ca,Mg,Na,K,Zn,P,S and Cl.Some factors affecting the changes of these elements were considered,including time,elemental correlations,weekday,weekend and seasonal changes.Diagnostic analysis provided an insight into a decoupling behavior that occursin siliceous and carbonates minerals.A decrease in Si and Al and an increase in carbonates,Na,K,Zn and P were observed during the cold season.However,a consistently high correlation of Si and Al was observed in all seasons.It was established that such high levels originated from street surface abrasion.The increase in variability and absolute levels of carbonates during the cold season was demonstrated by adding carbonates to the street surface as gritting material to increase the grip on snowy surfaces.A marked increase in Na and Cl was observed in winter which may have been caused by thaw salt that is widely used in winter in Austria.This was associated with a significant increase in K,Zn,and P in the cold season that was the result of domestic space heating with wood.PM10 levels in December were 12 μg/m3 and were higher than levels detected in July.It was established that such high levels originated from mineral oxides,wood smoke,and inorganic ionic material(s).     

广州市区公交车站PM_(2.5)与CO暴露水平研究

用便携式颗粒物浓度测定仪(DustTrak Model8520)和CO测定仪(Q-Trak Model8551),于2008年9月至2009年1月对广州市区11个代表性公交车站的PM2.5和CO暴露水平进行了测定。结果表明,公交车站7:00～19:00时间段PM2.5的平均浓度范围为206～348μg/m3,总体均值达288μg/m3,显示公交车站PM2.5污染问题突出;CO平均浓度范围1.5～4.0mg/m3,总体平均2.8mg/m3,有六个站点平均浓度超过了我国环境空气质量标准限值(4.0mg/m3或3.2mg/m3)。大多数站点工作日与非工作日PM2.5与CO水平差异不大,部分站点则受车流量和客流量变化影响呈现差异。同一站点PM2.5日变化特征不如CO明显,一次污染物CO变化受交通高峰影响呈双峰特征,而PM2.5水平影响因素复杂,一般白天较低,夜晚21:00出现峰值。不同站点CO与车流量未见显著相关性,表明车流量并不是决定公交站点CO水平的唯一因素,而扩散条件及公交车排放可能也是重要影响因素;与CO不同,不同站点PM2.5与车流量表现出显著相关(p0.05),可能侧面反映路面扬尘对公交车站PM2.5水平的影响和贡献。