首钢烧结厂PM10治理技术与经济分析

通过对首钢烧结厂的污染结点、污染物特性、污染物控制技术措施和技术规范进行分析,提出了烧结厂PM10控制方案,对烧结厂采用高效除尘设备的PM10削减量及改造费用进行了估算,确定了烧结厂PM10治理技术方案排序,为钢铁企业烧结厂治理颗粒污染物的同时选择最为经济实用的除尘器类型提供理论依据。     

首钢烧结厂PM10治理技术与经济分析

通过对首钢烧结厂的污染结点、污染物特性、污染物控制技术措施和技术规范进行分析，提出了烧结厂PM₁₀控制方案，对烧结厂采用高效除尘设备的PM₁₀削减量及改造费用进行了估算，确定了烧结厂PM₁₀治理技术方案排序，为钢铁企业烧结厂治理颗粒污染物的同时选择最为经济实用的除尘器类型提供理论依据。     

丽水市大气污染的时空分布特征及与气象要素的相关分析

利用2007-2010年丽水市逐日大气污染物浓度数据和地面气象观测资料,对PM10、SO2、NO23种大气污染物浓度进行了时空分布特征研究,进而探讨了气象要素对大气污染的影响.结果表明:2007-2010年,丽水市主要的3种大气污染物的负荷为PM10＞ NO2 ＞SO2,影响大气环境质量的污染物以PM10为主；总体来说,NO2的月均浓度基本达到《环境空气质量标准》(GB3095-1996)-级标准,冬半年(9-12月、1-2月)SO2的月均浓度仅达到二级标准,而夏半年(3-8月)月均浓度基本达到一级标准,PM10的月均浓度都达到二级标准(0.10 mg/m3)；在空间分布上,PM10、NO2的年均浓度都表现出东向西逐渐减少的特征,而SO2年均浓度主要体现为南向北递增的特征,3种大气污染物在空间上都表现为在东部缙云、青田等地的污染相对严重,而在西面的遂昌、龙泉等地的污染程度较轻;各种气象要素对大气污染的影响中,除了气压与3种大气污染物的浓度呈极显著正相关外,其他气象要素都表现为负相关,只是影响程度有所差异.气象要素对大气污染的影响不是单一作用的,而是通过多种气象要素相互配合、相互作用、综合反应来产生作用的.     

和田绿洲沙尘暴强度及其影响因子分析——以墨玉县为例

以和田绿洲西北部的墨玉县为研究区域,对该地区2016—2018年发生的沙尘暴天气资料以及气象因子(气温、风速、湿度、气压、水汽压、日照时数)和大气污染物(PM2.5、PM10、SO2、NO2、CO、O3)进行分析。结果表明,墨玉县沙尘暴天气主要发生在春夏季(3—8月),平均占全年发生频率的77.12%。墨玉县沙尘暴强度主要由气象因子决定,特别是气温、风速、日照时数和湿度。沙尘暴强度与大气颗粒物(PM10和PM2.5)存在着明显的间接关系,主要因为两者均受风速影响较大,沙尘暴强度越大,大气中PM10和PM2.5浓度越高。沙尘暴强度与SO2、NO2、CO、O3等大气污染物的关系非常微弱,但O3与沙尘暴的形成季节比较一致。     

污染物排放削减潜力评估方法——以中小型钢铁企业为例

根据中国中小型钢铁企业污染物排放情况,确立了污染物排放削减潜力评估方法。采用污染物排放削减潜力的数学模型,计算当前生产水平下实施清洁生产和末端治理后对SO2产生量和烟粉尘排放量的削减率,并预测中长期实施清洁生产和末端治理后,污染物产生量和排放量的削减潜力。结果表明,通过采取清洁生产措施和末端治理技术,中小型钢铁企业2020年在4种不同模式下,SO2产生量削减率分别为61.8%、66.4%、73.3%、84.7%;烟粉尘排放量削减率分别为37.9%、44.1%、53.4%、68.9%。通过污染物排放削减潜力的初步研究,不仅从宏观层次上说明了实施清洁生产和末端治理技术的积极意义,而且计算出不同经济发展模式下污染物产生量和排放量的削减量,为行业或区域污染物总量的指标分配和总量控制方案的制订提供了参考依据。     

冬季沈阳市典型源排放PM_(10)浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月~2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明:冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。     

冬季沈阳市典型源排放PM10浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月～2007年2月的PM10排放浓度资料，利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明：冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时，污染物扩散范围大，污染物浓度小；地势不平、风速小时，污染物扩散范围小，污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份，污染物分布主要集中在市区的北部、东部和南部地区，东部地区大气污染最为严重。     

杭州城市大气消光系数和能见度的影响因子研究

为了解杭州市能见度下降与大气污染之间的关系，在2001年5月至2002年5月对不同粒径的颗粒物（PM10、PM2.5）的质量浓度进行了观测，结合晴天天气条件下的大气能见度，推算污染物和水汽分子对大气的消光散射，发现细微颗粒物的散射消光特性对杭州市能见度下降起主要作用，并得到能见度与细微颗粒物浓度比值（PM2．5／PM10）的关系；分析了大气能见度和消光系数与PM2．5／PM10和相对湿度的相关系数。     

杭州城市可吸入颗粒物污染与气象条件关系的分级评价和BP神经网络评估

为了解杭州城市环境空气质量与气象条件之间的关系,利用杭州市区2003-2007年的可吸入颗粒物(PM10)浓度数据和气象资料,通过分级评价的方法和基于BP神经网络的污染物浓度评估模型,得到PM10浓度与气象条件的对应关系.结果表明,随着日降水量的增大,PM10浓度减小;风速与PM10浓度呈明显的负相关,随着风速的增大,PM10浓度明显减小;气象因素与PM10浓度之间呈非线性关系,大气能见度对PM10和相对湿度的变化极为敏感.随着PM10浓度的增大,大气能见度迅速降低,相对湿度越高,大气能见度则越低;近几年杭州市气象条件不利于大气污染物的扩散和清洗,是杭州城市环境空气质量上升缓慢的主要原因之一.     

燃煤工业锅炉大气污染物控制方案研究

基于中国燃煤工业锅炉大气污染物排放及治理现状,并结合国家相关产业政策和国内外技术发展趋势,以2008年为基准年,分析测算了2015、2020年燃煤工业锅炉大气污染物排放量,提出了适合中国国情的燃煤工业锅炉大气污染物控制技术路线.依据研究的控制方案,2015年,烟尘、二氧化硫及氮氧化物排放量分别为507万、458万、230万t；2020年,烟尘、二氧化硫及氮氧化物排放量分别为491万、423万、269万t.与2008年相比,大气污染物排放量变化不大,基本上做到了增容不增污.在此基础上,提出了燃煤工业锅炉大气污染物防治建议.     

Application of a combined measurement and modeling method to quantify windblown dust emissions from the exposed playa at Mono Lake, California

Particulate matter < or =10 microm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 microg/m3 (slope = 0.89, R2 = 0.77).     

Monitoring and source apportionment of particulate matter near a large phosphorus production facility

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM10. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM10 mass, 24-hr PM2.5 and PM10-2.5 mass and chemistry, continuous PM10 and PM2.5 mass, continuous meteorological data, and wind-direction-resolved PM2.5 and PM10 mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM10 exceedances, though in general, resuspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.     

Estimating the contribution of industrial facilities to annual PM10 concentrations at industrially influenced sites

If measures to reduce the industrial discharge of PM10 shall be planned with high accuracy, a first step must be to estimate the contribution of single industrial facilities to the overall PM10 burden as accurately as possible. In northern Duisburg as an example, an area where iron and steel producing industry is concentrated, PM10 was measured at 4 sampling sites very close to an industrial complex of blast furnaces, a sinter plant, oxygen steel works and a coke oven plant for 9 months in 2006. At two sites metals in PM10 were determined. The results, together with analytical data of urban background sites in the region and data of wind direction and wind speed were used for an estimation of the contribution of single plants to the PM10 burden. A careful analysis of the data showed, that the data of PM10, calcium, iron and zinc measured at two sites close to the industrial area and information about the urban background aerosol were sufficient to calculate the PM10 contribution of the main single plants. The data could be compared with those of modelling.     

Patterns and concentrations of PM10 in a mountainous basin region

In this study, continuous data of PM10 (particles with aerodynamic diameter < 10 microns) concentration measurements for a 4-yr period were analyzed. These measurements have been carried out in the Eordea Basin, an industrial area in the northwestern mountainous region of Greece. The annual, monthly, and diurnal patterns are presented and investigated regarding the prevailing meteorological conditions and atmospheric processes that affect the ambient concentrations of PM10. The effect of wind on controlling PM10 concentration is also discussed. Based on the data analysis, an attempt is made to provide useful information about air quality levels, taking into account U.S. Environmental Protection Agency air quality standards.     

Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston

An exposure study of 18 subjects with chronic obstructive pulmonary disease (COPD) living in the Boston, MA, area was conducted. The objective was to examine determinants of personal exposures to particulate matter (PM) with aerodynamic diameters of less than 2.5 microm (PM2.5), less than 10 microm (PM10), and between 2.5 and 10 microm (PM2.5-10). In a previous publication, the analyses of the longitudinal individual-specific relationships among indoor, outdoor, and personal levels showed that the relationships varied by subject and by particle size fraction. In the present paper, statistical and physical models were used to examine personal PM2.5, PM10, and PM2.5-10 exposure covariates. Results indicated that time-weighted indoor concentrations were significant predictors of personal PM2.5, PM10, and PM2.5-10 exposures. Also, time-weighted outdoor concentrations, time spent near smokers, and time spent during transportation were important predictors for PM2.5 but not for personal PM2.5-10 exposures. In turn, time spent cleaning contributed to all size-fraction personal exposures, whereas cooking affected only personal PM2.5-10 exposures. The findings showed that the relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates (or by ventilation status). Because the particle properties or components causing the health effects are unknown, it is not certain to what extent the risk posed by ambient particles can be reduced by controlling any one of these factors.     

Analysis of PM10, PM2.5, and PM2 5-10 concentrations in Santiago, Chile, from 1989 to 2001

Daily particle samples were collected in Santiago, Chile, at four urban locations from January 1, 1989, through December 31, 2001. Both fine PM with da < 2.5 microm (PM2.5) and coarse PM with 2.5 < da < 10 microm (PM2.5-10) were collected using dichotomous samplers. The inhalable particle fraction, PM10, was determined as the sum of fine and coarse concentrations. Wind speed, temperature and relative humidity (RH) were also measured continuously. Average concentrations of PM2.5 for the 1989-2001 period ranged from 38.5 microg/m3 to 53 microg/m3. For PM2.5-10 levels ranged from 35.8-48.2 microg/m3 and for PM10 results were 74.4-101.2 microg/m3 across the four sites. Both annual and daily PM2.5 and PM10 concentration levels exceeded the U.S. National Ambient Air Quality Standards and the European Union concentration limits. Mean PM2.5 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March); whereas coarse particle levels were similar in both seasons. PM concentration trends were investigated using regression models, controlling for site, weekday, month, wind speed, temperature, and RH. Results showed that PM2.5 concentrations decreased substantially, 52% over the 12-year period (1989-2000), whereas PM2.5-10 concentrations increased by approximately 50% in the first 5 years and then decreased by a similar percentage over the following 7 years. These decreases were evident even after controlling for significant climatic effects. These results suggest that the pollution reduction programs developed and implemented by the Comisión Nacional del Medio Ambiente (CONAMA) have been effective in reducing particle levels in the Santiago Metropolitan region. However, particle levels remain high and it is thus imperative that efforts to improve air quality continue.     

Concentrations of particulate matter emitted from large cattle feedlots in Kansas

Particulate matter (PM) emitted from cattle feedlots are thought to affect air quality in rural communities, yet little is known about factors controlling their emissions. The concentrations of PM (i.e., PM2.5, PM10, and total suspended particulates or TSP) upwind and downwind at two large cattle feedlots (KS1, KS2) in Kansas were measured with gravimetric samplers from May 2006 to October 2009 (at KS1) and from September 2007 to April 2008 (at KS2). The mean downwind and net (i.e., downwind - upwind) mass concentrations of PM2.5, PM10, and TSP varied seasonally, indicating the need for multiple-day, seasonal sampling. The downwind and net concentrations were closely related to the moisture content of the pen surface. The PM2.5/PM10 and PM2.5/TSP ratios at the downwind sampling location were also related to the moisture content of the pen surface, humidity, and temperature. Measurement of the particle size distribution downwind of the feedlot with a cascade impactor showed geometric mean diameter ranging from 7 to 18 microm, indicating that particles that were emitted from the feedlots were generally large in size.     

Fine and coarse particulate matter chemical characterization in a heavily industrialized city in central Mexico during Winter 2003

This paper presents the results of the first reported study on fine particulate matter (PM) chemical composition at Salamanca, a highly industrialized urban area of Central Mexico. Samples were collected at six sites within the urban area during February and March 2003. Several trace elements, organic carbon (OC), elemental carbon (EC), and six ions were analyzed to characterize aerosols. Average concentrations of PM with aerodynamic diameter of less than 10 microm (PM10) and fine PM with aerodynamic diameter of less than 2.5 microm (PM2.5) ranged from 32.2 to 76.6 [g m(-3) and 11.1 to 23.7 microg m(-3), respectively. OC (34%), SO4= (25.1%), EC (12.9%), and geological material (12.5%) were the major components of PM2.5. For PM10 geological material (57.9%), OC (17.3%), and SO4= (9.7%) were the major components. Coarse fraction (PM,, -PM2.5), geological material (81.7%), and OC (8.6%) were the dominant species, which amounted to 90.4%. Correlation analysis showed that sulfate in PM2.5 was present as ammonium sulfate. Sulfate showed a significant spatial variation with higher concentrations to the north resulting from predominantly southwesterly winds above the surface layer and by major SO2 sources that include a power plant and refinery. At the urban site of Cruz Roja it was observed that PM2.5 mass concentrations were similar to the submicron fraction concentrations. Furthermore, the correlation between EC in PM2.5 and EC measured from an aethalometer was r(2) = 0.710. Temporal variations of SO2 and nitrogen oxide were observed during a day when the maximum concentration of PM2.5 was measured, which was associated with emissions from the nearby refinery and power plant. From cascade impactor measurements, the three measured modes of airborne particles corresponded with diameters of 0.32, 1.8, and 5.6 microm.