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.     

Field performance of woodburning stoves in crested butte,Colorado

The carbon monoxide (CO) and particulate matter (PM) emissions of woodburning stoves have been measured under field conditions. Both conventional airtight stoves and newly installed airtight stoves certified by the U.S. Environmental Protection Agency to be low emitters of PM were monitored. The certified stoves were of two types, catalytic and noncatalytic. Compared to the conventional stoves, PM emission rates (g/hr) were reduced approximately 70% by both types of certified stoves. The CO emission rates were reduced 71% and 53% by catalytic and noncatalytic stoves respectively. These rate reductions occur because the certified stoves burn cleaner (less pollutant formation per kg of wood burned) and the average burn rate of certified stoves in field use is less than the average burn rate of conventional stoves.     

Traffic emission factors of ultrafine particles: effects from ambient air

Ultrafine particles have a significant detrimental effect on both human health and climate. In order to abate this problem, it is necessary to identify the sources of ultrafine particles. A parameterisation method is presented for estimating the levels of traffic-emitted ultrafine particles in terms of variables describing the ambient conditions. The method is versatile and could easily be applied to similar datasets in other environments. The data used were collected during a four-week period in February 2005, in Gothenburg, as part of the G?te-2005 campaign. The specific variables tested were temperature (T), relative humidity (RH), carbon monoxide concentration (CO), and the concentration of particles up to 10 μm diameter (PM(10)); all indicators are of importance for aerosol processes such as coagulation and gas-particle partitioning. These variables were selected because of their direct effect on aerosol processes (T and RH) or as proxies for aerosol surface area (CO and PM(10)) and because of their availability in local monitoring programmes, increasing the usability of the parameterization. Emission factors are presented for 10-100 nm particles (ultrafine particles; EF(ufp)), for 10-40 nm particles (EF(10-40)), and for 40-100 nm particles (EF(40-100)). For EF(40-100) no effect of ambient conditions was found. The emission factor equations are calculated based on an emission factor for NO(x) of 1 g km(-1), thus the particle emission factors are easily expressed in units of particles per gram of NO(x) emitted. For 10-100 nm particles the emission factor is EF(ufp) = 1.8×10(15)×(1 - 0.095×CO - 3.2×10(-3)×T) particles km(-1). Alternative equations for the EFs in terms of T and PM(10) concentration are also presented.     

Inventory of emissions of primary air pollutants in the city of Kocaeli, Turkey

This study aims to obtain a reliable inventory of the emission rates of the principal air pollutants including PM, SO2, NOx) and CO in Kocaeli, Turkey. In the first stage, the pollutant sources classified as point, area and line sources are determined in the area. Then the annual emission rates of the pollutants released from these sources are estimated by the emission factors given by USEPA and CORINAIR. Results show that the annual emission rates for PM, SO2, NOx) and CO are 2195 tons, 5342 tons, 14632 tons and 23095 tons, respectively. On the other hand, the pollutant group with the highest contribution to total emission rate is determined as the point sources for NOx, which is responsible for 73% of total NOx emission, while it is the area sources for PM, SO2 and CO with the contribution percentages of 75, 76 and 69, respectively.     

佛山市交通CO2排放及低碳出行对策

以佛山市2012年数据为基础,结合COPERT模型,分析了车型种类、排气量、燃油类型、排放水平等对CO2排放因子的影响规律,探讨了不同车型组成与排放水平下的CO2排放分担率,讨论并评估了佛山市的低碳交通出行对策。结果表明:排放水平对CO2排放因子的影响不明显,除重型客车与公交车,燃油类型对CO2排放因子的影响亦不明显,各车型的CO2排放因子随着排气量的增加而增加;当佛山市机动车平均行驶速度提高至55 km/h时,每辆车CO2综合排放因子可达最小值125.73 g/km;轻型客车和摩托车的CO2排放量最大,分别为1469 493 t/a和394 174.3 t/a,分担率分别为52.1%和14.0%;不同排放水平的载客车CO2排放分担率从大到小排序依次为:国I国0国Ⅱ国Ⅲ国Ⅳ,分别为34.7%、22.0%、21.2%、17.5%及4.6%。     

污染源减排对长三角区域冬季细颗粒物污染的敏感性研究

为了进一步精准有效地降低细颗粒物浓度,针对长三角区域细颗粒物PM2.5浓度,选取8个省级区域的5种污染物为减排目标,设定5个基准排放情景,采用CMAQ-DDM敏感性技术分别进行敏感性分析。结果表明,冬季长三角区域PM2.5污染受区域内的4个省级区域一次PM2.5排放影响最大,区域外的排放影响主要来自河南省和山东省的氨气和一次PM2.5。分别削减本地60%一次PM2.5的排放,安徽省PM2.5平均质量浓度下降了23. 24μg/m^3,江苏省下降了18. 32μg/m^3,上海市下降了15. 17μg/m^3,浙江省下降了9. 07μg/m3。综合各省(市)浓度响应曲线,最大排放因子均为本地一次PM2.5,削减20%左右存在敏感性最大值,削减60%之后浓度曲线趋于平缓,其他因子削减40%以后PM2.5浓度下降逐渐明显,对最后一位排放因子的响应则比较平缓。     

Integrated assessment of brick kiln emission impacts on air quality

This paper presents monitoring results of daily brick kiln stack emission and the derived emission factors. Emission of individual air pollutant varied significantly during a firing batch (7 days) and between kilns. Average emission factors per 1,000 bricks were 6.35–12.3 kg of CO, 0.52–5.9 kg of SO₂ and 0.64–1.4 kg of particulate matter (PM). PM emission size distribution in the stack plume was determined using a modified cascade impactor. Obtained emission factors and PM size distribution data were used in simulation study using the Industrial Source Complex Short-Term (ISCST3) dispersion model. The model performance was successfully evaluated for the local conditions using the simultaneous ambient monitoring data in 2006 and 2007. SO₂ was the most critical pollutant, exceeding the hourly National Ambient Air Quality Standards over 63 km² out of the 100-km² modelled domain in the base case. Impacts of different emission scenarios on the ambient air quality (SO₂, PM, CO, PM dry deposition flux) were assessed.     

成渝地区一次区域重污染过程来源解析及减排效果研究

基于嵌套网格空气质量预报模式(NAQPMS)及耦合的污染来源追踪模块模拟2017年12月16日至2018年1月3日成渝地区一次区域重污染过程,定量解析成渝地区主要城市PM2.5来源,评估过程中应急减排的成效。结果表明,天气静稳和风向辐合是造成此次重污染过程的重要因素,污染峰值阶段,成渝地区多个城市PM2.5日均质量浓度超过150μg/m3,达到重度污染级别。污染过程中,成都市PM2.5本地排放的贡献率为42%,眉山和德阳贡献率将近30%;重庆市PM2.5本地排放的贡献率为60%,外来输送以湖北、湖南和其他地区为主,贡献率为24%,成都和重庆市的工业源和交通源的贡献最大。区域联防联控应急减排对成渝各城市空气质量改善效果显著,成渝地区PM2.5浓度降低率为5%~11%,对于未实施应急预警方案的地区(如眉山市)受周边城市减排影响,浓度降低可达6%。     

Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity Delhi

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990–2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO₂, PM, and NO _x are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO₂, PM and NO _x respectively shows a reasonably satisfactory performance of the present estimates.     

A combined analysis to identify airborne PM10 sources

A two step procedure that combines an air dispersion model with a receptor model was used to identify the key sources that contribute to air levels of suspended particulate matter. The contribution to PM(10) concentrations measured at four monitoring sites in San Nicolas, Argentina, of the following sources, a thermal power plant, an integrated steel mill, motor vehicle exhaust fumes, and finally dust from paved and unpaved roads, have been analysed. Moreover, an air dispersion model was used to estimate the contribution of the thermal power plant, emissions of which have been described in depth by means of hourly fuel consumption and specific emission factors. The ratio "apportionment coefficient" was introduced to relate the contribution of this source to the measured 24 h PM(10) concentrations by analysing the frequency of occurrence of connecting winds between the power plant and each monitoring site. In San Nicolas 70% of the PM(10) sampled at three of the four monitoring sites could be attributed to the power plant in those scenarios where winds connected the facility's tall point sources with the sampling locations. The contribution to the measured PM(10) levels of the rest of the sources that are present in the analysed area was confirmed by way of receptor models. For this purpose, the multielemental composition of 41 samples was determined by Wavelength Dispersive X-ray Fluorescence analysis. In order to ascertain the underlying correlations between PM(10) samples and potential sources, Principal Component Analysis was performed on the standard matrix of composition profiles, which comprises the measured PM(10) samples being enlarged with the composition profiles of the potential contributing sources. The diagonalization of the covariance matrix was used as a screening procedure to differentiate the most likely contributing sources from those that were not significant.     

Air Quality and Monitoring Strategy in the Helsinki Metropolitan Area, Finland

The Helsinki Metropolitan Area Council (YTV) is responsible for air quality monitoring in the Helsinki area. Air quality has been monitored periodically since the late 1950s. An automatic SO2 monitoring network was constructed in 1975 and TSP measurements were added in 1978. Since then the network has been expanded and currently five automatic multicomponent stations form the basis of the network monitoring SO2, NO, NO2, CO, PM10 and O3 concentrations. Manual TSP and PM10 measurements are also conducted. Mobile monitoring units are also being used as well as special measurement campaigns. The effects of air pollution on nature are studied in bioindicator monitoring. An air quality index is used in order to inform the public of the current air quality situation. Changes in air quality are reflected in monitoring strategy. SO2 concentrations have decreased in the past two decades. Annual averages in 1995 were at or below 5 µg/m3. Traffic is the major source for pollutants even though catalytic converters have lowered traffic emissions somewhat. The highest annual average NO2 concentration at an urban site was 49 µg/m3 in 1995, and there has been no clear change in NO2 levels. There has been a decreasing trend in CO concentrations. Maximum annual TSP and PM10 averages in 1995 were 92 and 32 µg/m3, respectively. The highest average lead concentration was 0.01 µg/m3. Elevated concentrations are experienced from time to time. During the spring daily TSP and PM10 concentrations can go up to around 300 and 150 µg/m3, respectively. This is caused by resuspension mainly due to street sanding. Also a major winter NO2 episode occurred in December 1995. The highest hourly NO2 concentrations reached 400 µg/m3.     

Impact of CNG implementation on PAHs concentration in the ambient air of Delhi: A comparative assessment of pre- and post-CNG scenario

The use of alternative fuel is considered to be an effective measure to improve the urban air quality. Concerned over deteriorating air quality in Delhi, the Delhi government initiated different measures including stringent emission norms, improved fuel quality and above all introduction of cleaner fuel-CNG in public transport system. The entire city bus fleet was converted to CNG mode by 2002. The present study reports the comparative assessment of the status of air quality with respect to PM(10) and PAH before and after the introduction of CNG in public transport system in Delhi. The study has been carried out for two different time periods: first in the year 1998 and second in the year 2004. Following the total conversion of public transport system to CNG in 2002, Post-CNG data indicate a sharp reduction of 51-74% in the PM(10) concentration and 58-68% in the TPAH concentration as compared to the Pre-CNG data.     

上海市机动车污染实时排放预警系统设计与应用

研究上海市机动车污染的动态排放测算和网格化动态排放清单构建,在实时的交通数据和交通环境监测数据的基础上,结合交通模型、机动车排放清单模型等业务模型和算法,依托大数据存储、可视化和GIS等技术,开发了上海市机动车污染物实时排放预警系统,实现了上海市全市道路的机动车动态排放测算、交通环境政策实施情景模拟和网格化排放清单,更新频率为每30 min一次,包含PM、NOx、CO、SO2、VOCs等污染物和9种车型。系统建成后直接服务于首届中国国际进口博览会,为大气污染排放实时总量跟踪评估、污染源管控措施分析及监测成因分析等提供了有力的实时数据和技术支撑。     

北京地区PM10与秸秆燃烧排放单颗粒对比分析

采用场发射带能谱扫描电镜(FESEM/EDS)法分析北京怀柔地区PM10与秸秆燃烧排放颗粒的形貌特征和成分差异.结果显示:秸秆燃烧后排放颗粒物多为大粒径颗粒,成分上都含S、Cl和K元素.含有生物质燃烧标志元素K的PM10颗粒物多为含Si、Al和Na元素的燃煤飞灰和矿物颗粒,与秸秆燃烧排放颗粒组成化学元素差异明显.据此推...     

Aspiration and sampling efficiencies of the TSP and louvered particulate matter inlets

An experimental system was developed for the rapid measurement of the aspiration/transfer efficiency of aerosol samplers in a wind tunnel. We attempted to measure the aspiration and particle transfer characteristics of two inlets commonly used for sampling airborne Particulate Matter (PM): the 'Total Suspended Particulate' or TSP inlet, and the louvered 'dichotomous sampler inlet' typically used in sampling PM10 or PM2.5. We were able to determine the fraction of the external aerosol that enters the inlet and is transferred through it, and hence is available for collection by a filter, or further size fractionation into PM10 or PM2.5. This 'sampling efficiency' was analysed as a function of dimensionless aerodynamic parameters in order to understand the factors governing inlet performance. We found that for the louvered inlet the sampling efficiency increases as the external wind increases. Under all conditions expected in practical use the louvered inlet aspirates sufficient PM to allow either PM10 or PM2.5 to be selected downstream. The TSP inlet's sampling efficiency decreases with increasing external wind, and the TSP inlet is likely to under-sample the coarse end of the PM10 fraction at moderate and high external winds. As this inlet is generally not used with a downstream size fractionator, changes in sampling efficiency directly affect the measured aerosol concentration. We also investigated whether it is possible to dimensionally scale the PM inlets to operate at either higher or lower flow rates, while preserving the same sampling characteristics as the current full-scale, 16.67 L min(-1) versions. In the case of the louvered inlet, our results indicate that scaling to lower flow rates is possible; scaling to higher flow rates was not tested. For the TSP sampler, the sampling efficiency changes if the sampler is scaled to operate at smaller or larger flow rates, leading to unreliable performance.     

Reducing health risk assigned to organic emissions from a chemical weapons incinerator

Organic emissions from a chemical weapons incinerator have been characterized with an improved set of analytical methods to reduce the human health risk assigned to operations of the facility. A gas chromatography/mass selective detection method with substantially reduced detection limits has been used in conjunction with scanning electron microscopy/energy dispersive X-ray spectrometry and Fourier transform infrared microscopy to improve the speciation of semi-volatile and non-volatile organics emitted from the incinerator. The reduced detection limits have allowed a significant reduction in the assumed polycyclic aromatic hydrocarbon (PAH) and aminobiphenyl (ABP) emission rates used as inputs to the human health risk assessment for the incinerator. A mean factor of 17 decrease in assigned human health risk is realized for six common local exposure scenarios as a result of the reduced PAH and ABP detection limits.     

Investigation into presence of atmospheric particulate matter in Marikana, mining area in Rustenburg Town, South Africa

An investigation to find out presence of particulate matter in Marikana, a mining area in Rustenburg town, South Africa, was carried out in the months of August and November of 2008. Samples were collected for measurements of particulate matter (PM) of particle diameters of PM10, PM2.5, and PM1. After gravimetric analysis of daily measurements, it was found that PM10 concentration values ranged between 3 and 9 ??g/m³, PM2.5 concentration values ranged between 16 and 26 ??g/m³, and PM1 concentration values ranged between 14 and 18 ??g/m³ for the month of August 2008. For the month of November, it was found that PM10 concentration values ranged between 2 and 8 ??g/m³, PM2.5 concentration values ranged between 0 and 5 ??g/m³, and PM1 concentration values ranged between 4 and 15 ??g/m³. This study was undertaken as preliminary work having in mind that mining activities could be emitting high levels of particulate matter in the atmosphere which might be degrading the quality of the air. It was observed, however, that the daily particulate matter especially of PM10 emitted were quite low when compared to laid down International Air Quality Standards. The standards did not give guidelines for particulate matter of diameter 2.5 ??m. It was concluded that particulate matter came from three major sources: platinum mining, domestic biomass burning, and traffic emissions due to fuel burning.     

2020年江苏省机动车排放污染分布特征及与大气质量耦合性研究

依据生态环境部2021年6月发布的《排放源统计调查产排污核算方法和系数手册》,结合本地实测数据,在对汽油车颗粒物(PM)排放系数进行测算的基础上,核算了2020年江苏省机动车PM、氮氧化物(NO_(X))、挥发性有机物(VOC_(S))的排放总量,分析了机动车排放污染分布特征及与大气质量的耦合关系。结果表明:2020年江苏省机动车PM、NO_(X)、VOC_(S)排放量分别为0.5×10^(4),3.71×10^(5),1.17×10^(5) t。从区域分布来看,苏州、南京、无锡3市的3项污染物排放总量及NO_(X)、VOC_(S)排放量均位列前3位,PM排放量位列前3位的是苏州、徐州、无锡。从车型、燃料类型和排放阶段来看,国Ⅳ及以下排放标准的汽油小型客车是机动车VOC_(S)排放控制的重点,国Ⅲ排放标准的重型柴油货车是机动车PM和NO_(X)排放控制的重点。分析区域机动车PM排放量与大气中PM_(2.5)来源解析结果的耦合关系,其间存在不同程度的正相关性,控制机动车污染对改善大气环境会产生积极成效,南京、徐州和盐城3市的成效会尤为明显。     

降雨对长三角区域PM2.5浓度的影响

利用WRF-CAMx模式分析首届中国国际进口博览会(简称进博会)期间一次降雨过程对长三角地区PM2.5浓度影响,结果表明,降雨量分布区域与因降雨造成的PM2.5浓度减少量分布区域并不完全一致,湿沉降量受降雨量、PM2.5浓度和风速等多个因素共同影响。数值模拟结果表明,降雨导致浓度下降幅度排前5位的组分分别是有机气溶胶、硫酸盐、硝酸盐、铵盐和细颗粒原生气溶胶,下降幅度分别为44. 28%、16. 55%、11. 55%、9. 53%和5. 23%。结合观测资料和数值模式模拟结果可知,首届进博会期间上海本地减排和周边区域协同控制作用使PM2.5日均质量浓度降低33. 23μg/m3,因降雨引起的湿沉降作用使上海市PM2.5质量浓度降低15. 88μg/m^3。     

Indoor air quality assessment in child care and medical facilities in Korea

In order to characterize the status of indoor air pollution in some important facilities, a list of key criteria pollutants [particulate matter (PM(10)), carbon dioxide (CO(2)), carbon monoxide (CO), formaldehyde (HCHO), and bioaerosol] was measured from a total of 91 randomly selected sites in 18 different cities, Korea (February 2006 to December 2009). The target facilities include 43 child care facilities, 38 medical facilities, 6 elementary schools, and 4 postnatal care centers. The results showed that some air pollutants (e.g., CO and HCHO) did not exceed the recommended guideline [e.g., the Korean indoor air standard (KIAS) values of 10 ppm and 100 ppb, respectively]. However, concentration of PM(10), CO(2), and bioaerosol occasionally exceeded their respective guidelines (e.g., seven, three, and two cases). Discrete seasonalities were observed from indoor pollutants because of varying ventilation practice (e.g., summer time dominance of PM(10), HCHO, and bioaerosol or winter dominance of CO(2) and CO). However, as the concentrations of the indoor pollutants were scarcely above the recommended guideline level, more diversified approaches are desirable to diagnose the status of indoor pollution and to provide a realistic strategy for the improvement of IAQ.