武汉市大气污染变化趋势预测

以2014年武汉市大气污染源排放清单为基准,结合《武汉市城市空气质量达标规划（2013-2027年）》研究工作,预测了其实施后在控制"两高"行业新增产能、污染源综合治理、淘汰落后产能、控制机动车保有量等方面对武汉市SO₂、NO_x、PM₁₀、PM_2.5的减排量.利用嵌套网格空气质量预报模式系统（NAQPMS）,模拟分析了《达标规划》大气污染治理重点工程实施的空气质量改善效果.结果表明：《达标规划》实施后,2020年武汉市SO₂、NO₂、PM₁₀和PM_2.5排放量将分别比2014年削减22%~66%、6%~37%、14%~40%和17%~46%;武汉市空气质量有所改善,但NO₂和颗粒物年均浓度仍不能达到环境空气质量二级标准.     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

三亚地区冬春季大气污染特征观测研究

为了研究海南省三亚地区冬春季大气污染状况,于2011年12月—2013年4月的冬春季节在三亚鹿回头村(监测点位于三亚市郊,三面临海,周围没有工业污染源)开展了大气主要污染物(NO_x、O₃、PM_2.5)的连续监测,利用观测数据对三亚地区冬春季大气污染变化特征进行分析.结果表明:三亚地区大气污染物浓度均低于国家一级标准的浓度值,NO、NO₂、NO_x、O₃、PM_2.5质量浓度的日平均值(平均值±标准差)分别为(2.1±2.2)、(5.2±3.4)、(7.3±3.8)、(59.8±28.4)和(17.5±14.3)μg·m^-3.在污染物的日变化方面,NO_x、PM_2.5呈现典型的双峰型,其峰值分别出现在08:00和17:00,峰谷在13:00;O₃的日变化为单峰型,峰值出现在13:00.通过后向轨迹分析发现,三亚地区大气污染物受局地源排放和外源输送的共同影响,来自陆地的气流易造成污染物的积累,而来自海上的气流则有利于污染物的清除.     

福建三明市春季PM2.5中有机碳、元素碳和水溶性离子特征分析

2014年3月13日至4月20日在福建三明市利用PM_2.5中流量采样器采集大气中PM_2.5膜样品,测定了PM_2.5的质量浓度,并用热/光碳分析仪和离子色谱分析了其组分变化特征.结果表明,三明市观测期间PM_2.5的平均质量浓度为73.61±0.73 μg/m³,有机碳(OC)和元素碳(EC)的平均质量浓度分别为7.26±1.00和5.63±0.27 μg/m³,水溶性离子中SO₄^2-、NH₄⁺、NO₃^-和Na⁺的质量浓度分别为18.08±12.19、4.18±3.56、2.77±1.16和2.73±0.23 μg/m³,总和占总水溶性离子的87.76%.结合后向轨迹分析了福建三明市的污染物来源特征.该地区OC/EC的平均比值小于2,SOC(二次有机碳)生成量很少,主要以一次有机污染物为主,OC、EC与K⁺的相关性分析表明OC、EC与K⁺的来源相近,可以判断OC、EC绝大部分来源是生物质燃烧产生的污染物.在水溶性离子分析中,观测期间NO₃^-/SO₄^2-为0.159±0.02,表明三明市主要以固定源为主,机动车辆等移动源贡献较少.     

武汉市一次霾污染过程不同发展阶段下水溶性离子来源解析

本文利用气体组分及大气气溶胶在线监测系统(MARGA ADI 2080)观测武汉市2018年1月9—26日大气气溶胶中的8种水溶性离子(NH⁺₄、NO^-₃、SO^2-₄、Cl^-、K⁺、Ca²⁺、Na⁺和Mg²⁺),结合气象要素数据,使用主成分分析(PCA)、正定矩阵因子分析法(PMF)、HYSPLIT后向轨迹模式、潜在源区贡献(PSCF)和浓度权重轨迹(CWT),对霾污染过程中水溶性离子进行了全面的来源解析,探究了霾不同阶段下来源差异和空间分布特征。结果表明:(1)本次霾污染中的8种水溶性离子和4种污染气体,PCA解析出的源和占比分别为二次源和燃煤源的混合源(41.28%)、工业排放和土壤扬尘混合源(27.73%)和机动车排放源(9.63%),PMF解析出的源和占比分别为燃煤与土壤扬尘混合源(18.57%)、机动车排放源(20.74%)、二次源(18.30%)、光化学污染源(22.24%)和燃煤源(20.15%)。(2)霾在不同阶段下水溶性离子和4种污染气体的来源存在差异,在清洁天和霾消散阶段,光化学的贡献最高,占比分别为31.42%和36.07%;在霾发生阶段燃煤与土壤扬尘源的贡献最高,其贡献为40.94%;在霾发展阶段,最大的控制源为二次源,贡献占比为37.51%。(3)此次武汉市霾污染中PM_2.5浓度和NH⁺₄、NO^-₃和SO^2-₄的潜在源区为皖豫鄂三省和赣湘鄂三省交界处。霾污染中PM_2.5的主要影响范围是武汉市南部和北部省份,NO^-₃、NH⁺₄和SO^2-₄的主要影响区域为武汉市东北方向的城市、湖南省和江西省。     

基于CMAQ-MCM模型的长三角地区夏季臭氧和大气氧化性影响的研究

传统的空气质量模型多使用简化的光化学反应机制来模拟大气污染物的形成.这些机制主要基于烟雾箱实验拟合的反应速率和产物来模拟二次产物（如臭氧（O₃））前体物的氧化反应,具有一定的不确定性,导致模拟结果产生偏差.针对该问题,本研究将详细的大气化学机理（MCMv3.3.1）与美国国家环境保护局研制的第三代空气质量预报和评估系统CMAQ相结合（CMAQ-MCM）,模拟研究长三角地区2015年8月27—9月5日臭氧高发时段的空气质量.CMAQ-MCM模型可以较好地模拟长三角地区6个代表城市O₃和其前体物随时间的变化趋势.对模拟的O₃日最大8 h平均浓度的统计分析表明,徐州表现最好（标准平均误差=-0.15,标准平均偏差=0.23）.在长三角地区,居民源对挥发性有机物（VOCs）的贡献最大,占39.08%,其次是交通运输（33.25%）和工业（25.56%）.能源对总VOCs的贡献最小,约为2.11%.对活性氧化氮（NO_y）的分析表明,其主要组分是NO_x（80%）,其次是硝酸（HNO₃）（<10%）.O₃的空间分布与NO_y和NO_x非常相似.HCHO等其他氧化产物的分布与NO_x相似,这很可能是由于在高NO_x条件下VOCs氧化产生的产物.甲基乙烯基酮（MVK）和甲基丙烯醛（MACR）的空间分布与自然源VOCs （BVOCs）非常相似,表明长三角地区MVK和MACR主要由BVOCs氧化生成.长三角地区受到人为源和自然源排放相互作用的影响.     

冬季南京北郊大气气溶胶中水溶性阴离子特征

2009年冬季在南京北郊进行24 h采样,运用离子色谱法研究大气PM₁₀中水溶性阴离子的分布特征。结果表明:PM₁₀中阴离子的平均总质量浓度在白天和夜间分别为658.21、622.84 μg/m³;PM_2.1则分别为337.86、319.97 μg/m³,阴离子主要存在于细粒子中;主要水溶性阴离子均为SO₄^2-,且海盐对南京北郊大气PM₁₀和PM_2.1中的SO₄^2-质量浓度影响很小。SO₄^2-、Cl^-和F^-粒径谱分布相似,均呈双模态;NO₃^-和NO₂^-主要呈现单模态。SO₄^2-与NO₃^-、F^-与NO₃^-、SO₄^2-与Cl^-的相关系数均大于0.8,相关显著,说明其存在一定的同源性。NO₃^-/SO₄^2-的平均值在白天、夜间分别为0.058 2、0.048 4,说明南京北郊大气污染以固定源为主。分析NO₃^-、SO₄^2-前体物的转化率知道,采样期间SOR和NOR的平均值均大于10%,即SO₄^2-部分来源于SO₂的二次转化,而不是单一来源于一次污染物。     

武汉市冬季灰霾期PM2.5中水溶性无机离子的特征

2018年1月,利用颗粒物采样器采集武汉市大气PM_2.5样品并进行水溶性无机离子（F^-、Cl^-、NO₃^-、SO₄^2-、Na⁺、NH₄⁺、K⁺、Mg²⁺、Ca²⁺）的分析.结果表明,NO₃^-、SO₄^2-、NH₄⁺是PM_2.5中最主要的3种水溶性无机离子,除Mg²⁺与Ca²⁺外,PM_2.5与WSⅡs （水溶性无机离子）之间的相关性显著,且移动源贡献占主导地位.阴阳离子平衡表明武汉市冬季灰霾期PM_2.5呈中性或弱酸性.通过混合单粒子拉格朗日综合轨迹模式模拟并采用分层聚类得出了4种主要的后向气流轨迹及相应的PM_2.5和水溶性离子浓度,结果表明区域传输对此次灰霾期影响较大.     

北京秋季一次典型大气污染过程多站点分析

多站点多种大气污染物的同步在线观测对深入剖析大气污染的成因和演变机制有重要意义。以龙潭湖、北京325 m塔、双清路和阳坊4监测站点实时NO_x、SO₂、O₃、PM2.5和PM10浓度观测数据为基础,介绍了北京地区2010年10月3～11日发生的一次典型污染过程。不同污染物在污染过程中变化特征不一致,表现为NO_x、SO₂、O₃浓度有明显日变化,而PM浓度升高后一直维持在高值,日变化幅度很小。通过分析不同站点、相同污染物之间的相关性和变异系数发现,4站点间一次污染物NO和SO₂空间浓度差别大,变异系数分别为77%和70%,相关系数低于0.44;而二次污染物NO₂、PM2.5、O₃空间浓度差别较小,变异系数分别为34%、36%和29%,相关系数均超过0.54。结合中尺度气象模式研究发现,该污染过程中,850 hPa高空持续的西南暖平流造成华北地区显著平流逆温,与近地层辐射逆温共同作用,使北京地区混合层高度维持在1200 m以下。低混合层高度和低风速限制了大气垂直和水平扩散,造成北京地区近地层污染物累积,形成重度污染。     

短寿命气候强迫因子的自然源排放及气候反馈:IPCC AR6解读

短寿命气候强迫因子(Short-lived Climate Forcers,SLCFs)对大气污染和气候变化具有重要影响,政府间气候变化专门委员会(IPCC,2021)第六次评估报告(AR6)首次专门设立了关于SLCFs的独立章节,除了对人为源SLCFs评估以外,报告也包含了对于自然源SLCFs及其气候反馈的评估。特别地,在未来气候变暖和人为SLCFs持续减排的背景下,加深对SLCFs的自然源排放及其气候反馈的认识将更为重要。本文从自然源SLCFs排放评估、历史和未来气候情景下的排放变化、SLCFs的气候反馈几个方面解读了AR6中有关的最新结论。未来气候变暖情形下,闪电源NO_x、植被源BVOCs、生物质燃烧排放将会增加,土壤源NO_x、沙尘、海盐颗粒物和二甲基硫(Dimethlysulfide,DMS)对于气候变化的敏感性难以定量。同时,气候变化驱动着SLCFs的排放量、大气含量或寿命的改变,这些过程整体上造成的负反馈参数为-0.20 W/m²/℃(-0.41～+0.01 W/m²/℃),可能从一定程度上缓解气候变暖。     

Investigating the Changes in Air Pollutant Emissions over the Beijing-Tianjin-Hebei Region in February from 2014 to 2019 through an Inverse Emission Method

In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei(BTH)region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ens...     

不同人为源排放清单对大气污染物浓度数值模拟的影响:以浙江省为例

应用大气化学模式WRF-Chem(Weather Research and Forecast-Chemistry),分别选用亚洲排放源清单INTEX-B(Intercontinental Chemical Transport Experiment-Phase B)、REASv2.1(Regional Emission inventory in Asia version 2.1)以及全球排放源清单HTAP_v2(Hemispheric Transport of Air Pollution version 2),对浙江省2013年12月进行模拟,分别记为IN、RE和HT试验,研究人为源排放清单对大气污染物浓度数值模拟的影响。结果表明,3组试验合理的反映出PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物,即细颗粒物)、PM10(空气动力学当量直径小于等于10μm的颗粒物,即可吸入颗粒物)和NO_2近地面浓度的时空分布特征,相关系数为0.5~0.8,85%以上的模拟值落在观测值的0.5~2倍范围内,但对SO_2近地面浓度模拟较差。IN、RE、HT试验对PM2.5和PM10的模拟偏差均成递减趋势,约为30%、16%和6%,HT试验的模拟值更加接近观测。INTEX-B清单中PM2.5的一次排放与二次气溶胶前提物SO_2均高于REAS与HTAP清单,因此会导致更多的硫酸盐生成,从而进一步增加PM2.5浓度。HTAP_v2清单中较低的NH3排放会抑制硝酸盐的生成,从而有助于降低PM2.5浓度。3个清单的基准年与模拟年的差异对SO_2浓度模拟的准确性影响更大,INTEX-B清单中SO_2排放量明显高于REASv2.1与HTAP_v2清单,尤其在浙北和沿海工业发达地区,导致IN试验模拟的SO_2在这些地区存在明显高估。3组试验模拟的NO_2浓度偏差最小且更为接近(-8%~4%),主要原因是3个清单在浙江省的NOx排放十分一致。从3组试验结果之间的差异程度来看,浙江省范围内PM2.5、PM10、SO_2和NO_2逐日浓度模拟值之间的平均差异程度分别约为14%、15%、51%和16%,最大差异程度分别为69%、78%、137%和132%。月均浓度与逐日浓度的平均差异程度基本一致,但最大差异程度明显更低。总体来看3组试验模拟的PM2.5、PM10与NO_2的差异程度明显低于SO_2。     

Particulate matter and gaseous pollutants during a tropical storm and air pollution episode in Southern Taiwan

Gaseous pollutants and PM_2.5 aerosol particles were investigated during a tropical storm and an air pollution episode in southern Taiwan. Field sampling and chemical analysis of particulate matter and gaseous pollutants were conducted in Daliao and Tzouying in the Kaohsiung area, using a denuder-filter pack system during the period of 22 October to 3 November 2004. Sulfate, nitrate and ammonium were the major ionic species in the PM_2.5, accounting for 46 and 39% of the PM_2.5 for Daliao and Tzouying, respectively. Higher PM_2.5, Cl^?, NO₃^? and NH₄⁺, HNO₂ and NH₃ concentrations were found at night in both stations, whereas higher HNO₃ was found during the day. In general, higher PM_2.5, HCl, NH₃, SO₂, Cl^?, NO₃^?, SO₄^2? and NH₄⁺ concentrations were found in Daliao. The synoptic weather during the experiment was first influenced by Typhoon NOCK-TEN, which resulted in the pollutant concentrations decreasing by about two-thirds. After the tropical thunderstorm system passed, the ambient air quality returned to the previous condition in 12 to 24 h. When there was a strong subsidence accompanied by a high-pressure system, a more stable environment with lower wind speed and mixing height resulted in higher PM_2.5, as well as HNO₂, NH₃, SO₄^2?, Cl^?, NO₃^?, NH₄⁺ and K⁺ concentrations during the episode days. The rainfall is mainly a scavenger of air pollutants in this study, and the stable atmospheric system and the high emission loading are the major reasons for high air pollutant concentrations.     

Characteristics of the chemical composition and source apportionment of PM2.5 for a one-year period in Wuhan,China

In this study, 123 PM_2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM_2.5 concentration was 80.5?±?38.2 μg/m³, with higher PM_2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM_2.5 mass concentration, respectively. SO₄^2?, NO₃^? and NH₄⁺ were the dominant components, accounting for 40.2% of PM_2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO₃^?/SO₄^2? was 0.86?±?0.72, indicating that stationary sources play dominant role on PM_2.5 concentration. The ratio of OC/EC was 2.9?±?1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM_2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

     

Determination of the uncertainties of the German emission inventories for particulate matter and aerosol precursors using Monte-Carlo analysis

This paper presents the application of a Monte-Carlo simulation for assessing the uncertainties of German 2005 emissions of particulate matter (PM₁₀ & PM_2.5) and aerosol precursors (SO₂, NO_x, NH₃ and NMVOC) carried out in the PAREST (PArticle REduction STrategies) research project. For the uncertainty analysis the German Federal Environment Agency’s emission inventory was amended and integrated with a model on the disaggregation of energy balance data. A series of algorithms was developed in order to make efficient and pragmatic use of available literature and expert judgement data for uncertainties of emission model input data. The inventories for PM₁₀ (95 %-confidence interval: ?16 %/+23 %), PM_2.5 (?15 %/+19 %) and NO_x (?10 %/+23 %) appear most uncertain, while the inventories for SO₂ (?9 %/+9 %), NMVOC (?10 %/+12 %) and NH₃ (?13 %/+13 %) show a higher accuracy. The source categories adding the most relevant contributions to overall uncertainty vary across the pollutants and comprise agriculture, mobile machinery in agriculture and forestry, construction sites, small businesses/carpentries, cigarette smoke and fireworks, road traffic, solvent use and stationary combustion. The PAREST results on relative uncertainties have been quoted in the German Informative Inventory Reports since 2012. A comparison shows that the PAREST results for Germany are within the range of (for NH₃: close below) other European countries’ results on air pollutant inventory uncertainties as reported in the 2013 Informative Inventory Reports.     

Stable Carbon Isotope Ratios and the Photochemical Age of Atmospheric Volatile Organic Compounds

Abstract

The dependence of ozone formation on the mixing ratios of volatile organic compounds (VOCs) and nitrogen oxides (NO_x) has been widely studied. In addition to the atmospheric levels of VOCs and NO_x, the extent of photochemical processing of VOCs has a strong impact on ozone levels. Although methods for measuring atmospheric mixing ratios of VOCs and NO_x are well established and results of those measurements are widely available, determination of the extent of photochemical processing of VOCs, known as photochemical age (PCA), is difficult. In this article a recently developed methodology for the determination of PCA for individual compounds based on the change in their stable carbon isotope composition is used to investigate the dependence between ozone and VOC or NO_x mixing ratios at a rural site in Ontario, Canada, during fall and winter. The results show that under these conditions the variability in VOC mixing ratios is predominantly a result of the varying impact of local emissions and not a result of changes in the extent of atmospheric processing. This explains why the mixing ratio of ozone shows no systematic dependence on the mixing ratios of VOCs or NO_x in this environment and at this time of the year.     

Water-soluble inorganic ions of size-differentiated atmospheric particles from a suburban site of Mexico City

During the MILAGRO campaign, March 2006, eight-stage cut impactors were used to sample atmospheric particles at Tecámac (T1 supersite), towards the northeast edge of the Mexico City Metropolitan Area, collecting fresh local emissions and aged pollutants produced in Mexico City. Particle samples were analyzed to determine total mass concentrations of Ca²⁺, Mg²⁺, NH₄ ⁺, K⁺, Cl^?, SO₄ ^2?, and NO₃ ^?. Average concentrations were 22.1 ± 7.2 μg m^?3 for PM₁₀ and 18.3 ± 6.2 μg m^?3 for PM_1.8. A good correlation between PM₁₀ and PM_1.8, without influence from wind patterns, indicates that local emissions are more important than the city’s pollution transported to the site, despite the fact that Tecámac is just 40 km away from Mexico City. A lack of diurnal patterns in the PM_2.5/PM_1.8 ratio supports this conclusion. The inorganic composition of particles suggests that vehicles, soil resuspension, and industries are the main pollutant sources. Finally, the particles were found to be neutralized, in agreement with observations in the Mexico City Metropolitan Area.     

PM2.5 co-benefits of climate change legislation part 1: California’s AB 32

The Scoping Plan for compliance with California Assembly Bill 32 (Global Warming Solutions Act of 2006; AB 32) proposes a substantial reduction in 2020 greenhouse gas (GHG) emissions from all economic sectors through energy efficiency, renewable energy, and other technological measures. Most of the AB 32 Scoping Plan measures will simultaneously reduce emissions of traditional criteria pollutants along with GHGs leading to a co-benefit of improved air quality in California. The present study quantifies the airborne particulate matter (PM_2.5) co-benefits of AB 32 by comparing future air quality under a Business as Usual (BAU) scenario (without AB 32) to AB 32 implementation by sector. AB 32 measures were divided into five levels defined by sector as follows: 1) industrial sources, 2) electric utility and natural gas sources, 3) agricultural sources, 4) on-road mobile sources and 5) other mobile sources. Air quality throughout California was simulated using the UCD source-oriented air quality model during 12 days of severe air pollution and over 108 days of typical meteorology representing an annual average period in the year 2030 (10 years after the AB 32 adoption deadline). The net effect of all AB 32 measures reduced statewide primary PM and NO_x emissions by ~1 % and ~15 %, respectively. Air quality simulations predict that these emissions reductions lower population-weighted PM_2.5 concentrations by ~6 % for California. The South Coast Air Basin (SoCAB) experienced the greatest reductions in PM_2.5 concentrations due to the AB 32 transportation measures while the San Joaquin Valley (SJV) experiences the smallest reductions or even slight increases in PM_2.5 concentrations due to the AB 32 measures that called for increased use of dairy biogas for electricity generation. The ~6 % reduction in PM_2.5 exposure associated with AB 32 predicted in the current study reduced air pollution mortality in California by 6.2 %, avoiding 880 (560–1100) premature deaths per year for the conditions in 2030. The monetary benefit from this avoided mortality was estimated at $5.4B/yr with a weighted average benefit per tonne of $35 k/tonne ($23 k/tonne–$45 k/tonne) of PM, NO_x, SO_x, and NH₃ emissions reduction.