Methods for determination of elemental carbon in ambient air

A few analytical methods of elemental carbon determination are described. The purpose of the work is to choose the best method for determination of its content in dust suspended in air in industrial regions. The reflectance and chromatographic methods were investigated. It was shown that the reflectance methods could be used only when the particle size and form of elemental carbons constant. The chromatographic method, which includes the step of combustion of the sample in oxygen and chromatographic determination of evolved CO₂ is recommended, since it is independent of the form of carbon. Organic carbon is removed from dust samples by extraction with benzene-methanol mixture.     

活性炭负载催化剂去除燃煤烟气中单质汞的研究

以贵州凯里褐煤进行燃烧实验,研究采用CoCl2(负载量20%)改性的活性炭去除烟气中的单质汞。颗粒态汞占烟气总汞的87%,而单质汞占气态汞的80.4%。改性活性炭吸附了气态汞中97%的单质汞,而吸收液只吸收了3%的单质汞。可见改性活性炭也能有效地吸附煤燃烧实验中的烟气汞。实验结果表明,煤中汞的释放率为59.5%,1kg的改性活性炭可以吸附208t煤所产生的烟气中的气态单质汞。     

秸秆焚烧对空气质量影响特征及判别方法的研究

利用南京空气自动监测数据及PM_(2.5)组分监测结果,分析了2011年夏收秸秆焚烧期间大气污染特征,并探寻快速判别秸秆焚烧影响的指标及方法。结果表明:秸秆焚烧期间PM_(2.5)污染特征显著,其组分中K~+、EC、OC等浓度相对偏高。基于离子组分及碳元素在线监测数据,可选取K~+作为快速判别指标,并根据K~+与PM_(2.5)的相关性,计算秸秆焚烧对PM_(2.5)的贡献。同时结合OC、EC浓度变化,综合判别秸秆焚烧对空气质量的影响程度。     

合肥市冬季细颗粒物中碳组分特征分析

利用2020年12月1日至2021年2月28日合肥市细颗粒物(PM_2.5)、有机碳(OC)和元素碳(EC)等环境空气质量监测数据和气象观测数据,分析了合肥市大气PM_2.5中OC和EC的污染特征,并探讨了其来源以及气象因素影响。结果表明：合肥市冬季碳质气溶胶是PM_2.5中主要组分,随着污染程度的加重,碳质气溶胶的质量浓度逐步增加,但其在PM_2.5中的占比先减小后增加。在以PM_2.5为首要污染物的不同污染级别天气条件下,OC和EC的相关性说明不同程度下碳质气溶胶来源复杂。OC/EC表明机动车尾气和燃煤源排放是碳质气溶胶的主要来源。二次有机碳(SOC)会随着污染程度的加重而呈现升高趋势。OC和EC在冬季受温度影响较小;较大的相对湿度对OC和EC具有一定的清除作用,明显降水或连续降水的清除作用更加显著;而风速对含碳气溶胶的影响主要出现在污染天气背景下。     

Measurement of particle concentrations in a dental office

Particles in a dental office can be generated by a number of instruments, such as air-turbine handpieces, low-speed handpieces, ultrasonic scalers, bicarbonate polishers, polishing cups, as well as drilling and air sprays inside the oral cavity. This study examined the generation of particles during dental drilling and measured particle size, mass, and trace elements. The air sampling techniques included both continuous and integrated methods. The following particle continuous measurements were taken every minute: (1) size-selective particle number concentration (Climet); (2) total particle number concentration (PTRAK), and; (3) particle mass concentration (DustTrak). Integrated particle samples were collected for about 5 h on each of five sampling days, using a PM_2.5 sampler (ChemComb) for elemental/organic carbon analysis, and a PM₁₀ sampler (Harvard Impactor) for mass and elemental analyses. There was strong evidence that these procedures result in particle concentrations above background. The dental procedures produced number concentrations of relatively small particles (<0.5 μm) that were much higher than concentrations produced for the relatively larger particles (>0.5 μm). Also, these dental procedures caused significant elevation above background of certain trace elements (measured by X-ray fluorescence) but did not cause any elevation of elemental carbon (measured by thermal optical reflectance). Dental drilling procedures aerosolize saliva and products of drilling, producing particles small enough to penetrate deep into the lungs. The potential health impacts of the exposure of dental personnel to such particles need to be evaluated. Increased ventilation and personal breathing protection could be used to minimize harmful effects.     

因子分析法解析北京市大气颗粒物PM10的来源

2004年10月份在北京市6个采样点采集了大气PM10样品,分析了大气颗粒物的质量浓度、元素组成、离子、有机碳(OC)和元素碳(EC)的浓度,并用因子分析模型对颗粒物的来源进行了研究。结果显示,北京市大气颗粒物的来源主要有6类:建筑水泥尘/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘、生物质燃烧尘和燃油尘。用模型计算得到的各源对PM10的贡献率分别为建筑水泥尘/机动车尾气尘/燃煤尘占36.57%、土壤风沙尘占16.07%、二次粒子尘占12.33%、工业粉尘占10.29%、生物质燃烧尘占6.07%、燃油尘占3.84%、其它占14.84%。其中建筑水泥/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘是大气颗粒物PM10的主要来源。实验表明,在缺少源成分谱时可以用因子分析模型来分析大气颗粒物的来源及其相对贡献。     

合肥市冬季灰霾天气PM_(2.5)源解析

于2016年12月30日—2017年2月4日,利用单颗粒气溶胶飞行时间质谱仪(SPAMS),对合肥市PM_(2.5)开展来源解析连续监测,共捕捉到4次较为明显的灰霾过程,对颗粒物种类及质谱特征进行了分析。结果显示,监测期间合肥市主要颗粒物成分为元素碳(EC)(31. 9%)、富钾(K)(16. 6%)、有机碳(OC)(16. 0%)及混合碳颗粒(ECOC)(15. 0%)等。主要污染源为机动车尾气源(24. 5%)、工业工艺源(22. 7%)、燃煤源(14. 1%)、二次无机源(13. 5%)等。污染天气发生时,工业工艺源占比上升2. 2个百分点,生物质燃烧和燃煤源占比分别下降1. 7和2. 7个百分点,机动车尾气和扬尘源基本持平,表明此次污染过程主要受到工业工艺源的累积影响。     

Chemical compositions and sources of atmospheric PM10 in heating, non-heating and sand periods at a coal-based city in northeastern China

Mass concentrations and chemical components (18 elements, 9 ions, organic carbon [OC] and elemental carbon [EC]) in atmospheric PM(10) were measured at five sites in Fushun during heating, non-heating and sand periods in 2006-2007. PM(10) mass concentrations varied from 62.0 to 226.3 μg m(-3), with 21% of the total samples' mass concentrations exceeding the Chinese national secondary standard value of 150 μg m(-3), mainly concentrated in heating and sand periods. Crustal elements, trace elements, water-soluble ions, OC and EC represented 20-47%, 2-9%, 13-34%, 15-34% and 13-25% of the particulate matter mass concentrations, respectively. OC and crustal elements exhibited the highest mass percentages, at 27-34% and 30-47% during heating and sand period. Local agricultural residuals burning may contribute to EC and ion concentrations, as shown by ion temporal variation and OC and EC correlation analysis. Heavy metals (Cr, Ni, Zn, Cu and Mn) from coal combustion and industrial processes should be paid attention to in heating and sand periods. The anion/cation ratios exhibited their highest values for the background site with the influence of stationary sources on its upper wind direction during the sand period. Secondary organic carbon were 1.6-21.7, 1.5-23.0, 0.4-17.0, 0.2-33.0 and 0.2-21.1 μg m(-3), accounting for 20-77%, 44-88%, 4-77%, 8-69% and 4-73% of OC for the five sampling sites ZQ, DZ, XH, WH and SK, respectively. From the temporal and spatial variation analysis of major species, coal combustion, agricultural residual burning and industrial emission including dust re-suspended from raw material storage piles were important sources for atmospheric PM(10) in Fushun at heating, non-heating and sand periods, respectively. It was confirmed by principal component analysis that coal combustion, vehicle emission, industrial activities, soil dust, cement and construction dust and biomass burning were the main sources for PM(10) in this coal-based city.     

Correlations in the chemical composition of rural background atmospheric aerosol in the UK determined in real time using time-of-flight mass spectrometry

An aerosol time-of-flight mass spectrometer (ATOFMS) was used to determine, in real time, the size and chemical composition of individual particles in the atmosphere at the remote inland site of Eskdalemuir, Scotland. A total of 51,980 particles, in the size range 0.3-7.4 microm, were detected between the 25th and 30th June 2001. Rapid changes in the number density, size and chemical composition of the atmospheric aerosol were observed. These changes are attributed to two distinct types of air mass; a polluted air mass that had passed over the British mainland before reaching Eskdalemuir, interposed between two cleaner air masses that had arrived directly from the sea. Such changes in the background aerosol could clearly be very important to studies of urban aerosols and attempts at source apportionment. The results of an objective method of data analysis are presented. Correlations were sought between the occurrence of: lithium, potassium, rubidium, caesium, beryllium, strontium, barium, ammonium, amines, nitrate, nitrite, boron, mercury, sulfate, phosphate, fluorine, chlorine, bromine, iodine and carbon (both elemental and organic hydrocarbon) in both fine (d < 2.5 microm) and coarse (d > 2.5 microm) particle fractions. Several previously unreported correlations were observed, for instance between the elements lithium, beryllium and boron. The results suggest that about 2 in 3 of all fine particles (by number rather than by mass), and 1 in 2 of all coarse particles containing carbon, consisted of elemental carbon rather than organic hydrocarbon (although a bias in the sensitivity of the ATOFMS could have affected these numbers). The ratio of the number of coarse particles containing nitrate anions to the number of particles containing chloride anions exceeded unity when the air mass had travelled over the British mainland. The analysis also illustrates that an air mass of marine origin that had travelled slowly over agricultural land can accumulate amines and ammonium.     

城市生活垃圾理化特性研究

本文对北京昌平冬季城市生活垃圾的理化特性进行了研究。测定了垃圾的物相组成,分析了垃圾中Ｃ、Ｈ、Ｏ、Ｎ、Ｓ的含量,进行了原生垃圾浸出毒性试验,测定了垃圾的发热量及其它化学性能,为探索城市垃圾的减量化、无害化、资源化的技术途径提供了技术支持。     

Monitoring cyclical air/water elemental mercury exchange

Previous experimental work has demonstrated that elemental mercury evasion from natural water displays a diel cycle; evasion rates during the day can be two to three times evasion rates observed at night. A study with polychlorinated biphenyls (PCBs) found that diurnal PCB air/water exchange rates exceeded nocturnal exchange rates by 32%. Given that the exchange rates of both PCBs and elemental mercury are dominated by the resistance in the aqueous thin film at the air/water interface and that water column elemental mercury concentrations in natural water bodies also display a diel cycle (and water column PCB concentrations do not) the findings here suggest that PCBs can serve as a tracer to assess the relative contribution of diel atmospheric temperature variations on elemental mercury air/water exchange rates. Using previously published data describing water column elemental mercury concentrations and the previously published diel mercury evasion model, four evasion scenarios are examined within the context of monitoring air/water toxicant exchange: constant atmospheric temperatures and constant water column elemental mercury concentrations; variable atmospheric temperatures and constant water column elemental mercury concentrations; constant atmospheric temperatures and variable water column elemental mercury concentrations; and variable atmospheric temperatures and variable water column elemental mercury concentrations. A scenario of monthly elemental mercury air/water exchange also is examined (at constant atmospheric and water column elemental mercury concentrations). Some of the findings include: (1) atmospheric temperature variations do have a significant effect on air/water toxicant exchange; (2) diel atmospheric temperature variations become more significant to overall diel toxicant exchange rates the closer the air/water system is to equilibrium conditions; (3) for refractory toxicants, average diel exchange rates are best estimated by averaging datasets obtained over a 24 h period or, at minimum, by measuring exchange rates at average atmospheric temperature values; (4) for elemental mercury, variable diel water column concentrations are likely to be the dominant contributor to variations in diel evasion rates; (5) diel atmospheric temperature variations amplify the magnitudes of both diel mercury evasion and absorption events and can shift maximum evasion rates to later in the day; (6) variations in monthly elemental mercury air/water exchange rates may exceed diel variations: and (7) 24 h and monthly monitoring efforts will likely be required to accurately describe diel and annual elemental mercury air/water exchange in a given system.     

Regional and seasonal characteristics of emission sources of fine airborne particulate matter collected in the center and suburbs of Tokyo, Japan as determined by multielement analysis and source receptor models

Airborne particulate matter, suspected to induce adverse effects on human health, have been one of the most important concerns regarding recent air pollution issues in Japan. To characterize regional and seasonal variations in emission sources of fine airborne particulate matter (d < 2 microm), monthly samples (n = 36 for each site) were collected at urban (Tokyo), suburban (Maebashi), and mountainous (Akagi) sites in Japan from April 2003 to March 2006. Multielement analysis of chemical species (Na, Al, K, Ca, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Sb, and Pb) was performed by inductively coupled plasma-atomic emission spectrometry and inductively coupled plasma-mass spectrometry. The combined source receptor model, which consists of positive matrix factorization and chemical mass balance, determined the contributions of nine emission sources (local and continental soils, road dust, coal and oil combustion, waste incineration, steel industry, brake wear, and diesel exhaust) to the observed elemental concentrations. Large regional differences were identified in the source contributions among the observational sites. Diesel exhaust was identified as the most significant source (70% of identified contributions) at the urban site. Local and continental soils, coal combustion, and diesel exhaust were intricately assigned (20-30% each) to the suburban site. Continental soil was the predominant source (65%) at the mountainous site. Respective significant source contributions dominated the seasonal variations of total elemental concentrations at each site. These results suggest that a better understanding of the regional and seasonal characteristics of impacting emission sources will be important for improving regional environments.     

大气乙醛碳同位素分析方法的研究

利用气相色谱/燃烧/同位素比值质谱(GC/C/IRMS)分析技术,采用NaHSO3与半胱胺衍生化方法,测定了气态乙醛在衍生化反应过程中的碳同位素效应,探讨了采用该方法测定大气乙醛碳同位素组成的可行性。试验测定了乙醛、衍生剂半胱胺及相应衍生物的碳同位素比值,结果表明,乙醛衍生物的δ13C测量值与理论值的偏差范围为0.11‰～0.35‰,在仪器精密度范围内(<0.50‰),即在衍生化过程中基本不会发生碳同位素分馏。采用该方法初步测定了大气中乙醛的碳同位素组成,实测数据显示,广州地化所和肇庆鼎湖山大气乙醛δ13C平均值分别为(-34.21±0.27)‰和(-31.23±0.16)‰,相同采样点的大气乙醛碳同位素组成基本不变,可见该方法可作为研究大气乙醛不同排放源的一种有效方法。     

新疆准东经济技术开发区二氧化碳排放现状与降碳对策研究

通过分析新疆准东经济技术开发区各行业的二氧化碳排放量及排放特征,研究新疆准东经济技术开发区碳达峰碳中和的实现路径。分析结果显示,准东经济技术开发区最主要的二氧化碳排放源是化石燃料燃烧,其对二氧化碳排放量的贡献比例在95.2%以上。能源活动二氧化碳排放量占总排放量的98.5%以上;工业生产过程排放的二氧化碳较少,占比在1.5%以下。新疆准东经济技术开发区主要二氧化碳排放行业是煤电、电解铝、煤化工、硅基新材料。在此基础上,结合各行业特点,提出发展园区循环经济、制定低碳行业标准和培育低碳产业等详细对策。     

Monitoring and dispersion modelling of emissions from the fluidised bed combustion of poultry litter

Gaseous emissions from the fluidised bed combustion of chickenlitter were monitored and recorded. Emission data was used tocreate a dispersion model for a proposed site on a poultry farmin Limerick, Ireland. Variables within the combustion unit notonly influenced combustion but also emission levels ofpollutants such as SO₂ and NO_x. CO emissions decreased withuse of the correct ratio between fluidising and secondary air,the staging of secondary air and the degree of turbulence withwhich the secondary air is introduced. Dispersion modelling ofactual combustion at a proposed poultry unit predicted thatground level concentrations for the set of emissions data wouldbe below the limits and guidelines set by air quality standards.This was true for both and line source. Line sourceconcentration levels were less than those for point source.     

Emission factors from residential combustion appliances burning Portuguese biomass fuels

Smoke from residential wood burning has been identified as a major contributor to air pollution, motivating detailed emission measurements under controlled conditions. A series of experiments were performed to compare the emission levels from two types of wood-stoves to those of fireplaces. Eight types of biomass were burned in the laboratory: wood from seven species of trees grown in the Portuguese forest (Pinus pinaster, Eucalyptus globulus, Quercus suber, Acacia longifolia, Quercus faginea, Olea europaea and Quercus ilex rotundifolia) and briquettes produced from forest biomass waste. Average emission factors were in the ranges 27.5-99.2 g CO kg(-1), 552-1660 g CO(2) kg(-1), 0.66-1.34 g NO kg(-1), and 0.82-4.94 g hydrocarbons kg(-1) of biomass burned (dry basis). Average particle emission factors varied between 1.12 and 20.06 g kg(-1) biomass burned (dry basis), with higher burn rates producing significantly less particle mass per kg wood burned than the low burn rates. Particle mass emission factors from wood-stoves were lower than those from the fireplace. The average emission factors for organic and elemental carbon were in the intervals 0.24-10.1 and 0.18-0.68 g kg(-1) biomass burned (dry basis), respectively. The elemental carbon content of particles emitted from the energy-efficient "chimney type" logwood stove was substantially higher than in the conventional cast iron stove and fireplace, whereas the opposite was observed for the organic carbon fraction. Pinus pinaster, the only softwood species among all, was the biofuel with the lowest emissions of particles, CO, NO and hydrocarbons.     

2020年泰州市细颗粒物质量浓度高值区污染来源解析

2020年在位于泰州市主城区大气细颗粒物(PM_(2.5))质量浓度高值区的莲花国控空气站点进行手工采样,分析了大气PM_(2.5)的质量浓度和元素组成,以及离子、有机碳和元素碳的质量浓度。根据监测结果,采用正定矩阵因子分解(PMF)受体模型对其来源进行解析。结果显示,莲花站点大气PM_(2.5)中主要组分包括有机物、硝酸盐、硫酸盐、铵盐、地壳物质、氯盐、钾盐、黑炭、微量元素和钠盐,占比分别为35.7%,25.6%,13.9%,11.9%,6.1%,2.3%,1.5%,1.5%,0.8%和0.7%,有机物、硝酸盐、硫酸盐、铵盐为首要污染组分,这4类物质对PM_(2.5)的累计贡献为87.1%。根据解析结果与实际污染特征,提出应优化城市路网结构,强化工地扬尘管控,全面取缔燃煤炉和严抓秸秆禁烧工作等控制对策。     

基于区域环境空气质量和碳排放数据的减污降碳协同效果评估

化石燃料燃烧产生的温室气体与大气污染物具有同根同源性,但具体治理中减污降碳的协同效果尚不明确。以浙江省11个设区市为研究样本,对环境空气质量和二氧化碳(CO₂)排放数据进行分析研究,结果显示：2016—2020年浙江省环境空气质量持续改善,但CO₂排放总量仍处于增长阶段。11个设区城市PM_2.5年均浓度降幅在26%～41%之间,二氧化氮(NO₂)年均浓度下降趋势不明显,大部分城市呈现碳排放增加、NO₂浓度下降的特征,只有杭州和温州两市呈现碳排放总量和NO₂、PM_2.5浓度协同下降的趋势。因子相关性分析结果表明,各设区市呈现NO₂浓度与碳排放相关性较大、协同性强,PM_2.5浓度与碳排放相关性较小的特点。进一步通过减污降碳协同定量评价分析表明,浙江地区在环境空气质量改善和温室气体减排已表现出一定成效,但各设区市因产业结构、环境基础条件、协同程度等不同导致减污降碳综合绩效有明显差异。从源头减排实现...     

Emission factor of mercury from coal-fired power stations

Mercury emission from coal-fired power stations, situated in Poland in the Silesian region was investigated. The determination methods for mercury in the consumed coal and in combustion gas, used in this research, are described. The mass of mercury emitted into the air from coal combustion in the power station is in constant relation to the mercury content in the consumed coal during the assumed period. A relationship between mercury emission into the air and the mercury content in the consumed coal in electric power stations is derived.     

宁波PM10中有机碳和元素碳的季节变化及来源分析

为了探讨宁波市大气颗粒物中浓度水平与季节变化,2010年1、5、8、11月分季节采集了宁波市大气中PM10样品,在宁波连续观测了PM10以及有机碳(OC)、元素碳(EC)的浓度变化,并探讨宁波全年各季碳气溶胶污染变化特征;PM10中OC和EC相关性较好,说明OC与EC的来源相同,各采样点PM10中OC/EC的各季均值大部分超过2.0,表明宁波空气中存在一定的二次污染。宁波秋季SOC占OC含量高于其他季节。从PM10中8个碳组分丰度初步判断宁波市颗粒物中碳的主要来源是汽车尾气、道路扬尘及燃煤。