规模化笼养蛋鸡舍冬季氨气和颗粒物排放特征研究

畜禽养殖的氨气(NH3)和颗粒物(particulatematter,PM)排放已成为危害人畜健康,并可能造成环境风险的重大问题。该文选择北京郊区一典型规模化蛋鸡养殖舍,对典型冬季条件下蛋鸡舍的NH3和PM排放进行了连续8d的监测;并根据二氧化碳平衡原理,对NH3及PM的排放通量进行了估算。研究结果表明,蛋鸡舍出风口处NH3平均质量浓度为(4.58±3.29)mg/m3,每只鸡NH3排放通量为(32.2±12.5)mg/d。蛋鸡舍出风口处PM2.5、PM10和总悬浮颗粒物(total suspended particulates, TSP)质量浓度为(0.13±0.06)、(0.81±0.16)、(3.28±1.32)mg/m3,每只鸡PM2.5、PM10和TSP排放通量分别为(0.7±0.4)、(6.3±1.4)、(27.6±12.5)mg/d。氨气以及PM的排放均随着舍内1次/2 d的机械清粪频率呈现2 d的周期变化趋势。除清粪作业、鸡群日间活动等影响外,舍内PM2.5浓度一定程度上受舍外环境本底值影响。舍内PM2.5与PM10的比例在10.4%~20.4%之间。舍内PM2.5颗粒上所含的K+、Mg2+含量均显著高于舍外环境本底PM2.5(P0.05)。同时舍内及舍外PM2.5颗粒上解析出来的阳离子所带的电荷量均高于阴离子。研究结果可为畜禽养殖NH3和PM排放清单的编制提供基础参数;同时对畜禽舍PM的组分研究,可为后续开展二次无机气溶胶形成机理以及颗粒物源解析的研究提供支撑。     

城市不同绿地PM2.5质量浓度日变化规律

以北京林业大学校园(绿地率42.2%)、奥林匹克森林公园(绿地率70.3%)和鹫峰国家森林公园(绿地率96.2%)为研究对象,以周边主要交通干道为对照,采用多功能精准型激光粉尘仪观测PM2.5质量浓度,研究城市不同绿地PM2.5质量浓度日变化规律。结果表明:1)绿地率对PM2.5质量浓度变化有较大影响,研究区内PM2.5质量浓度随绿地率增加而递减,北京林业大学校园、奥林匹克森林公园和鹫峰国家森林公园PM2.5质量浓度最高值分别为140、62和48μg/m3,均高于国家PM2.5质量浓度年平均标准(35μg/m3);2)研究区内城市绿地PM2.5质量浓度与其周边主要交通干道没有明显差异;3)气象条件对PM2.5质量浓度的变化有较大影响,阴天PM2.5质量浓度较高,长时间保持在80～110μg/m3之间,降雨天则使PM2.5质量浓度明显降低,降幅约达80%。     

大型自然通风奶牛舍空气颗粒物浓度监测方法中测点数和位置优化

对奶牛舍颗粒物浓度和分布进行实时连续监测,是评估其环境风险和制定科学减排措施的前提。随着大型奶牛舍的快速发展,对尽可能少且科学地布置测点数量和位置并能够对舍内颗粒物浓度进行精准监测,提出了新的挑战。为探究测点优化布置方案,该研究基于物联网技术在大型自然通风奶牛舍内3个相邻饲养区域布置17个采样点,对总悬浮颗粒物（total suspended particle, TSP）和细颗粒物（PM_2.5）浓度进行了连续6个月监测,得到舍内浓度平均值（视为“真值”）;利用系统聚类和误差分析方法得到优化的测点方案,并将其颗粒物浓度结果与6种传统测点方案进行对比,以确定最优的测点数量和位置方案。结果表明,舍内3个饲养区域内颗粒物浓度分布均匀,PM_2.5浓度在不同采样高度上无统计差异（P>0.05）,而TSP浓度在屋顶通风口下方（9.0 m）明显低于1.5和2.5 m高度（P<0.05）。与真值相比,优化测点方案的TSP和PM_2.5浓度监测误差绝对值之和分别为6.4%～22.6%和4.7%～14.2%,均低于传统测点方案。综合考虑优化方案的科学性和传统方案的易操作性,确定最优测点方案为：在奶牛舍中央屋顶通风口下方1.0～2.0 m处布置1个测点,在奶牛卧床上方2.5 m高度布置2个测点,上述3个测点按奶牛舍斜对角线进行布置;另外,分别在挤奶通道、饲喂通道、清粪通道上方2.5 m高度处各布置1个测点;共计6个测点。该优化测点方案可满足监测准确性和易操作性要求。     

北京市道路防护林带内外PM2.5质量浓度特征及与气象要素的相关性

以北京市奥林匹克森林公园北侧的北五环路防护林带为研究对象,通过在林带外及林带内布设5处PM2.5质量浓度监测点进行3个月的定位监测,分析北京市道路防护林带内外PM2.5质量浓度特征,并通过建立PM2.5质量浓度与风速、温度、相对湿度等气象要素的相关关系,分析气象要素对PM2.5质量浓度的相关性.结果表明：1）在时间变化规律上,林带内PM2.5质量浓度08：00和12：00相对较高,其他时间段相对较低,18：00后质量浓度又开始增加,林带内PM2.5质量浓度在日变化规律上呈单峰或双峰变化,林带内外PM2.5质量浓度的日变化规律基本一致;2）在空间变化规律上,林带内PM2.5质量浓度水平比林带外相对较高,距北五环路40 m处PM2.5质量浓度值相对其他布置点2、20、30和60m处都高;3）林带内PM2.5质量浓度与风速、温度呈负相关关系,与相对湿度、气压呈正相关关系;4）林带内PM2.5质量浓度与温度的关系可以用幂函数来描述.     

冬季采暖保育猪舍送排风管道组合换气系统设计与评价

为实现保育猪舍内局部环境通风调控,该研究设计一种垂直送排风管道组合换气系统。采用CFD(Computational Fluid Dynamics)技术对垂直管道通风模式下舍内的空气流场进行模拟,并以相对湿度和CO_2浓度作为输入变量建立通风模糊控制系统。模拟结果显示保育猪所在水泥地板区域风速保持在0.1～0.2 m/s。参照模拟结果,以猪栏为通风单元对保育猪舍通风系统进行改造,舍内气流不均匀性系数在0.1以下,表明采用该换气系统的保育猪舍通风均匀性较好;猪舍温度在21～25℃,相对湿度小于70%,NH_3浓度小于5mg/m~3,CO_2浓度小于1200mg/m~3,舍内各项环境参数适宜保育猪健康生长。系统运行功耗为270～1 150 W。现场测试与分析结果表明,该垂直送排风管道组合换气系统,可以精确控制猪舍环境,兼顾冬季猪舍通风与保温问题。     

育肥猪舍甲烷排放浓度和排放通量的测试与分析

畜禽养殖是重要的温室气体排放源，畜禽养殖的甲烷排放量受动物生长特性、粪便收集方式和气候条件的影响。为了探讨中国特有的饲养管理方式下育肥猪舍温室气体排放规律，为减少甲烷排放提供依据，该研究在北京选择一典型猪场，对不同季节育肥舍的甲烷排放浓度进行了试验测定，从2004年5月至2005年3月，每2个月一次连续采集72～80 h甲烷浓度和相关数据，并根据二氧化碳平衡原理，对猪场的甲烷排放量进行了估算。结果表明：育肥猪舍内甲烷浓度有明显的季节性和日变化特性，2005年1月舍内甲烷的平均浓度为(22.98±10.52)mg/m³，7月舍内甲烷浓度为(2.68±0.68)mg/m³；每日最低甲烷浓度出现在9:00 am～17：00 pm时段；冬季舍内二氧化碳浓度明显偏高，夜间比允许浓度高1倍；每头育肥猪饲养期间的甲烷排放量为68.10～207.01 mg/h，折合每标准动物单位排放量：436～1185 mg/h·(500 kg)，在IPCC推荐的发展中国家猪呼吸代谢甲烷排放1.0 kg/(a·头)范围内。     

少污水排放垫料猪舍生产和环境效果

针对传统猪舍污水产生量大、处理费用高问题,该文设计并建造了一种基于减少育肥猪生产过程中污水排放的猪舍,为了检验少污水排放猪舍的饲养和环境控制效果,以规模化猪场常规育肥猪舍为对照舍,对其春季和夏季的生产效果和环境效果进行了研究。结果表明：试验舍与对照舍夏季平均温度分别为26.6℃、27.0℃,相对湿度分别为77%、71%,春季平均温度分别为18.9℃、21.0℃,相对湿度分别为50%,49%,试验舍和对照舍内育肥猪的平均日增质量、料质量比基本相同;但少污水排放型猪舍具有明显的节水效果,单头猪夏季减少用水量13.2 L/d,春季减少用水量1.4 L/d,夏季减少污水量16.5 L/d,春季减少污水量4.7 L/d,,少污水排放型猪舍不影响育肥猪生长性能,但能较大的减少生产过程中的用水量和污水排放量。     

基于AOD数据的新疆大型露天煤炭开采区PM2.5和PM10反演

MODIS气溶胶产品AOD与PM2.5、PM10浓度高度相关,已广泛应用在PM2.5、PM10浓度模拟.该研究以新疆维吾尔自治区大型露天煤炭开采区准东矿区为研究对象,结合实测的2014年5月、7月、9月、12月PM2.5、PM10质量浓度数据与经过垂直湿度订正的MODIS气溶胶产品AOD,利用多元回归进行拟合建模,从建立的40个模型中选取最优模型并据此对研究区PM2.5、PM10的质量浓度进行定量估算.结果表明:AOD与PM2.5、PM10呈极显著正相关;4个月AOD与PM2.5、PM10质量浓度估算模型最优模型均为多项式模型;其中7月AOD与PM2.5质量浓度拟合模型较好(R2=0.6258),实测值与预测值拟合趋势线R2为0.8057;9月PM10拟合模型效果理想(R2=0.7329),实测值与预测值拟合趋势线R2为0.8077;将AOD代入最优模型反演PM2.5,从空间层面上反映出各区域PM2.5浓度差异明显.研究结果可为AOD的深度利用与PM2.5、PM10浓度的遥感估算提供参考,在大气污染物空间分布、监测大气环境质量、污染预测等方面都具有重要意义.     

大型自然通风奶牛舍空气颗粒物浓度监测方法中采样间隔优化

规模化奶牛养殖产生的颗粒物会对人员和奶牛的呼吸道以及周边环境健康产生不利影响。对于奶牛舍空气颗粒物的实时连续监测,除了监测点数量和位置外,监测设备的采样间隔同样会影响监测结果的准确性。为确定合理的采样间隔,该研究采用环境物联网技术在大型自然通风奶牛舍内共计布置了17个采样点,对秋季至冬季舍内的总悬浮颗粒物(total suspended particulate, TSP)和细颗粒物(PM_2.5)浓度进行连续6个月的实时监测,计算舍内17个采样点的平均浓度(视为“真值”)。基于误差分析法,分别计算了30 min和1、2、3、6、12 h采样间隔下秋季和冬季的颗粒物浓度日均值,以及10、15、20、30 min和1 h采样间隔下白天、夜间与生产管理操作期间的颗粒物浓度小时均值及其与真值的相对误差(E_r),统计了E_r在5%与10%范围内的占比情况,以66.7%作为可接受标准,确定了秋冬季节颗粒物浓度日均值和小时均值的最大可接受采样间隔。结果显示,在5%的相对误差允许范围内,秋冬季节TSP日均值的最大可接受采样间隔为2 h(秋季...     

道路绿化带内大气PM_(2.5)质量浓度变化特征

为了研究道路绿化带对大气PM2.5质量浓度变化的影响,在靠近五环路的北京市东升公园观测不同林带内PM2.5颗粒物的浓度变化,分析林带内外的PM2.5浓度变化特征以及植被结构配置对其的影响。结果表明,PM2.5颗粒物浓度的日变化基本一致,有明显的起伏,峰值出现在早上8:00和下午18:00,谷值出现在下午16:00左右;林内PM2.5浓度相比道路降低了10.49%,相较于纯林,混交林对PM2.5的阻滞作用更好。气象条件是影响PM2.5浓度的重要因素,在一定的范围内,PM2.5质量浓度随着温度的上升而下降,随着相对湿度的升高而增大。林带宽度对PM2.5的阻滞作用比较复杂,在0~20m林带宽度内,PM2.5浓度呈现上升趋势,在20~50m处,PM2.5浓度呈现下降趋势,50m外趋于稳定。单位面积三维绿量与PM2.5浓度呈负相关关系。     

Reductions of PM2.5 Air Concentrations and Possible Effects on Premature Mortality in Japan

The current study estimates premature mortality caused by long-term exposure to elevated concentrations of PM_2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 μm) in Japan from 2006 to 2009. The premature mortality is calculated based on a relative risk of 1.04 (95 % CI, 1.01–1.08) per 10 μg?m^?3 increase above the annual mean limit of 10 μg?m^?3 taken from the World Health Organization Air Quality Guidelines. The spatiotemporal variations of PM_2.5 are estimated based on the measurements of suspended particulate matter (SPM) (with aerodynamic diameter approximately less than 7.0 μm) at 1,843 monitors. The improvements of air quality in Japan by reducing the emissions of SPM from 2006 to 2009 could save 3,602 lives based on a reduction target of 10 μg?m^?3 annual mean concentration. This finding could be a tangible benefit gained by reducing the emissions of particulate matter in Japan.     

A Module to Calculate Primary Particulate Matter Emissions and Abatement Measures in Europe

Primary particulate matter is emitted directly into the atmosphere from various anthropogenic and natural sources such as power plants (combustion of fossil fuels) or forest fires. Secondary particles are formed by transformation of SO₂, NO_x, NH₃, and VOC in the atmosphere. They both contribute to ambient particulate matter concentrations, which may have adverse effects on human health. Health hazards are caused by small particulate size, high number of especially fine (< 2.5 µm) and ultra-fine (< 0.1 µm) particles and/or their chemical composition. As part of an integrated assessment model developed at IIASA, a module on primary particulate matter (PM) emissions has been added to the existing SO₂, NO_x, NH₃ and VOC sections. The module considers so far primary emissions of total suspended particles (TSP), PM₁₀ and PM_2.5 from aggregated stationary and mobile sources. A primary PM emission database has been established. Country specific emission factors for stationary sources have been calculated within the module using the ash content of solid fuels.     

An Assessment of the Mobile Source Contribution to PM10 and PM2.5 in the United States

Mobile sources are significant contributors to ambient particulate matter (PM) in the United States. As the emphasis shifts from PM₁₀ to PM_2.5, it becomes particularly important to account for the mobile source contribution to observed particulate levels since these sources may be the major contributor to the fine particle fraction. This is due to the fact that most mobile source mass emissions have an aerodynamic diameter less than 2.5 µm, while the particles of geological origin that tend to dominate the PM₁₀ fraction generally have an aerodynamic diameter greater than 2.5 µm. A common approach to assess the relative contributions of sources to observed particulate mass concentrations is the application of source apportionment methods. These methods include material balance, chemical mass balance (CMB), and multivariate receptor models. This paper describes a number recent source attribution studies performed in the United States in order to evaluate the range of the mobile source contribution to observed PM. In addition, a review of the methods used to apportion source contributions to ambient particulate loadings is presented.     

Monitoring of Submicron Particulate Matter Concentrations in the Air of Turin City, Italy. Influence of Traffic-limitations

Several studies have shown the association between ambient particulate matter (PM) and adverse health effects, thus highlighting the need to limit the anthropogenic sources of PM, especially motor vehicle emissions. PM exposure is commonly monitored as mass concentration of PM10 or PM2.5, although increasing toxicity with decreasing aerodynamic diameter has been reported. In the present study an analysis was performed of the concentration and size distribution of airborne PM fractions collected at street level in the city center of Turin, Italy, to verify the usefulness of “ecological” days with traffic limitations. PM levels were determined daily at five different outdoor sites, from Thursday to Tuesday for 7 weeks (five with “ecological” Sunday, two with normal traffic density). Air sampling was performed using a six-channel laser particle counter to determine the number of particles (n°/l) in six size ranges between 0.3 and 10 μm. Climatic conditions and indoor PM levels were also monitored. The PM size distribution was constant for all the samples tested, with the 90% of the particles smaller than 0.5 μm, suggesting that measurements for count are needed in addition to the traditional ones based on the mass. The total number of particles was highly variable comparing days or weeks of monitoring, but much less among the sites of air sampling. The restriction of motor vehicle circulation has not determined any significant effect on PM levels and, in the winter period, PM0.5 peak concentrations were measured also on the ecological days.     

PM10 and PM2.5 Levels in the Eastern Mediterranean (Akrotiri Research Station, Crete, Greece)

Particulate matter measurements (PM₁₀, PM_2.5) using a beta radiation attenuation monitor were performed at the Akrotiri research station (May 2003–March 2006) on the island of Crete (Greece). The mean PM₁₀ concentration during the measuring period (05/02/03–03/09/04) was equal to 35.0?±?17.7 μg/m³ whereas the mean PM_2.5 concentration (03/10/04–04/02/06) was equal to 25.4?±?16.5 μg/m³. The aerosol concentration at the Akrotiri station shows a large variability during the year. Mean concentrations of particulate matter undergo a seasonal change characterised by higher concentrations during summer [PM₁₀, 38.7?±?10.8 μg/m³ (2003); PM_2.5, 27.9?±?8.7 μg/m³ (2004) and 27.8?±?9.7 μg/m³ (2005)] and lower concentrations during winter [PM₁₀, 28.7?±?22.5 μg/m³ (2003/2004); PM_2.5, 21.0?±?13.0 μg/m³ (2004/2005) and 21.4?±?21.9 μg/m³ (2005/2006)]. Comparative measurements of the PM₁₀ concentration between the beta radiation attenuation monitor, a standardized low volume gravimetric reference sampler and a low volume sequential particulate sampler showed that PM₁₀ concentrations measured by the beta radiation attenuation monitor were higher than values given by the gravimetric samplers (mean ratio 1.17?±?0.11 and 1.21?±?0.08, respectively). Statistical and back trajectory analysis showed that elevated PM concentrations (PM₁₀, 93.8?±?49.1 μg/m³; PM_2.5: 102.9?±?59.9 μg/m³) are associated to desert dust events. In addition regional transport contributes significantly to the aerosol concentration levels whereas low aerosol concentrations were observed during storm episodes.     

棉秆燃烧过程中的颗粒物排放特性

该文利用滴管炉结合DEKATI低压撞击采样器,研究燃烧温度和原料粒径对棉秆燃烧过程中颗粒物排放特性的影响,并结合扫描电镜和X射线光谱分析仪探讨了颗粒物的微观结构和元素组成.结果表明PM1排放量随燃烧温度升高而显著降低,从68.90 mg/m3降低至14.02 mg/m3;颗粒物总排放量从75.41 mg/m3降低至16.30 mg/m3;颗粒物分布峰值从0.609μm附近移至0.261μm附近;原料粒径减小使得PM1排放量下降,从39.84 mg/m3降低23.06 mg/m3,而PM1-10排放量增加,从5.18 mg/m3增至8.38 mg/m3.分析表明细颗粒物(0.028~0.261μm)主要由K、Cl及少量S元素组成,形成途径主要为碱金属化合物如KCl、KOH及K2SO4等的蒸发-凝集作用,并呈现较规则的微观结构,存在形式主要为KCl;粗颗粒物(1.590~9.860μm)主要由Ca、Mg及少量Si、P组成,主要通过大颗粒的破碎或富Ca、Mg和Si颗粒物的异质凝结转化形成,多呈较规则的球形结构;中间段颗粒物(0.261~1.590μm)属于过渡段,介于细颗粒物和粗颗粒物之间,微观结构较为复杂.