川南四座城市PM2.5化学组分污染特征及其源解析

为探究川南地区大气气溶胶中化学组分与来源特征,于2015年9月—2016年8月在四川盆地南部4个典型代表城市(泸州、内江、宜宾、自贡)采集了226个PM_2.5样品,对PM_2.5的质量浓度和主要化学组分(水溶性离子和碳质组分)进行测定,并利用颗粒物源解析受体模型对PM_2.5来源进行解析.结果表明:川南地区PM_2.5日均浓度为46.4—68.0μg·m^-3,均高于国家环境空气质量标准年均PM_2.5限值(35.0μg·m^-3).OC、EC和水溶性二次离子(SO₄^2-、NO₃-和NH₄+)分别占PM_2.5质量的15.7%—22.8%、4.2%—6.4%和28.6%—55.8%.PM_2.5及其主要化学组分浓度有显著的季节变化,即冬季浓度显著高于其他季节,夏季浓度最低.泸州除夏季外,其他季节SO₄2-、NO₃-同源性较好;其他城市在冬季,SO₄2-、NO₃-同源性较好.NH₄+主要存在形式为NH₄NO₃、(NH₄)2SO₄、NH₄HSO₄.OC、EC来源复杂,主要为机动车源、煤燃烧源和生物质燃烧源.川南地区PM_2.5的来源主要受8种因子影响,按总体贡献排序依次为:二次硫酸盐、生物质燃烧、工业源、二次硝酸盐、机动车源、煤燃烧、道路尘埃和建筑尘埃.此外,相比较而言,机动车源贡献在泸州市较凸显,煤燃烧源贡献在宜宾市较凸显.     

辽宁西南典型城市冬季大气细颗粒物水溶性无机离子污染特征及来源解析

本研究于2018年12月3日-2019年1月1日在辽宁省西南典型城市葫芦岛市和朝阳市分别布设3个城区采样点,在区域传输点龙屯水库布设1个采样点,采集大气细颗粒物PM2.5样品(n=201).使用离子色谱检测样品中的Na+、Mg2+、Ca2+、K+、NH4+、SO42-、F-、Cl-和NO3-的质量浓度.观测期间PM2....     

Improving simulations of sulfate aerosols during winter haze over Northern China: the impacts of heterogeneous oxidation by NO2

Incorporating the missing heterogeneous oxidation of S(IV) by NO₂ into the WRF-Chem model. Sulfate production is not sensitive to increase in SO₂ emission. The newly added reaction reproduces sulfate concentrations well during winter haze. We implemented the online coupled WRF-Chem model to reproduce the 2013 January haze event in North China, and evaluated simulated meteorological and chemical fields using multiple observations. The comparisons suggest that temperature and relative humidity (RH) were simulated well (mean biases are -0.2K and 2.7%, respectively), but wind speeds were overestimated (mean bias is 0.5 m?s⁻¹). At the Beijing station, sulfur dioxide (SO₂) concentrations were overpredicted and sulfate concentrations were largely underpredicted, which may result from uncertainties in SO₂ emissions and missing heterogeneous oxidation in current model. We conducted three parallel experiments to examine the impacts of doubling SO₂ emissions and incorporating heterogeneous oxidation of dissolved SO₂ by nitrogen dioxide (NO₂) on sulfate formation during winter haze. The results suggest that doubling SO₂ emissions do not significantly affect sulfate concentrations, but adding heterogeneous oxidation of dissolved SO₂ by NO₂ substantially improve simulations of sulfate and other inorganic aerosols. Although the enhanced SO₂ to sulfate conversion in the HetS (heterogeneous oxidation by NO₂) case reduces SO₂ concentrations, it is still largely overestimated by the model, indicating the overestimations of SO₂ concentrations in the North China Plain (NCP) are mostly due to errors in SO₂ emission inventory.     

城市森林大气PM2.5中水溶性无机离子沉降特征

森林被誉为"地球之肺",在防霾治污方面有其独特不可替代的作用,不同树种沉降PM_2.5的功能有很大差别.本文选取代表性城市森林——奥林匹克森林公园为研究对象,设置垂直监测塔观测大气PM_2.5的浓度垂直分布,以考察不同季节城市森林对PM_2.5中各组分的影响.在冬季、春季和夏季各采集PM_2.5样品,分析并计算PM_2.5中Na⁺、NH₄⁺、K⁺、Mg2⁺、Ca2⁺、Cl^-、NO₃^-和SO₄^2-等典型水溶性无机离子的浓度.结果表明,PM_2.5中水溶性无机离子总浓度呈规律性变化特征:冬季((56.90±27.38)μg·m-3)>春季((46.69±12.24)μg·m^-3)>夏季((23.16±8.75)μg·m^-3).其中SO₄^2-和NO₃^-浓度和占PM_2.5主要水溶性无机离子总浓度的50%以上.3个季节中,除冬季外,在春季和夏季,8种离子有明显的垂直方向上的沉降,夏季的沉降速率高于春季,但是春季由于大气颗粒物浓度高,沉降通量高于夏季.NO₃^-和SO₄^2-垂直方向的沉降量在所有可溶性无机离子中最高.植被密度、叶面积指数、气象条件等因素对于PM_2.5的沉降特征有明显影响.     

济南市PM2.5中二次组分的时空变化特征及其影响因素

为分析济南市PM_2.5中二次组分的时空变化和影响因素,对济南市春季(2019年5月16—25日)、秋季(2019年10月15—24日)和冬季(2019年12月17—2020年1月16日)4个典型点位的PM_2.5样品进行连续采样,并测定了PM_2.5中水溶性离子、有机碳(OC)和元素碳(EC)的含量。结果表明:物流交通区的二次组分质量浓度最高(56.13μg·m^?3),钢铁工业区的二次组分浓度比城市市区高,但是二次组分占比较城市市区低,清洁对照点的浓度和占比最低;济南市4个功能区SO₄^2?和NO₃^?转化率均高于0.1,除清洁对照点外,城市市区、钢铁工业区和物流交通区的SO₄^2?转化率明显高于NO₃^?转化率;济南市春季、秋季和冬季的ρ(NO₃^?)/ρ(SO₄^2?)分别为0.67、2.57和1.98,春季PM_2.5浓度以固定源贡献为主,秋季和冬季以移动源贡献为主;运用ISORROPIA热力学模型分析了含水量和pH对二次组分生成的影响,含水量会随着污染增大而增大,酸度和含水量对二次无机组分的转化机理产生影响,酸度会抑制二次无机组分的生成,而含水量会促进二次组分的生成;后向轨迹聚类分析结果表明,占比最高的轨迹(29.2%)来自东北方向的滨州和东营,基于潜在源贡献因子(WPSCF)和浓度权重轨迹(WCWT)分析PM_2.5中二次组分质量浓度的潜在污染源区域,SO₄^2?的主要贡献源区在济南市区北部的济阳区和东北方向的滨州、东营等,NO₃^?和NH₄⁺的主要贡献源区在济南市区北方向的济阳区、东北方向的章丘区和南方向的莱芜区等。该研究结果可为中国北方城市细颗粒物进一步的治理和防控提供数据支撑和理论依据。     

Relations between indoor and outdoor PM2.5 and constituent concentrations

Factors impacting indoor-outdoor relations are introduced. Sulfate seems a fine tracer for other non-volatile species. Particulate nitrate and ammonium desorb during outdoor-to-indoor transport. OC load increases during the transport due to sorption of indoor SVOCs. Outdoor PM_2.5 influences both the concentration and composition of indoor PM_2.5. People spend over 80% of their time indoors. Therefore, to assess possible health effects of PM_2.5 it is important to accurately characterize indoor PM_2.5 concentrations and composition. Controlling indoor PM_2.5 concentration is presently more feasible and economic than decreasing outdoor PM_2.5 concentration. This study reviews modeling and measurements that address relationships between indoor and outdoor PM_2.5 and the corresponding constituent concentrations. The key factors in the models are indoor-outdoor air exchange rate, particle penetration, and deposition. We compiled studies that report I/O ratios of PM_2.5 and typical constituents (sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), elemental carbon (EC), and organic carbon (OC), iron (Fe), copper (Cu), and manganese (Mn)). From these studies we conclude that: 1) sulfate might be a reasonable tracer of non-volatile species (EC, Fe, Cu, and Mn) and PM_2.5 itself; 2) particulate nitrate and ammonium generally desorb to gaseous HNO₃ and NH₃ when they enter indoors, unless, as seldom happens, they have strong indoor sources; 3) indoor-originating semi-volatile organic compounds sorb on indoor PM_2.5, thereby increasing the PM_2.5 OC load. We suggest further studies on indoor-outdoor relationships of PM_2.5 and constituents so as to help develop standards for healthy buildings.     

Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

● This study explored the long-term association by double robust additive models. ● Individual exposure concentrations were assessed by integrating GAM, LUR and BPNN. ● PM_2.5, SO₂ and NO₂ are positively associated with cerebrovascular disease. ● CO could reduce the risk of cerebrovascular disease with the highest robustness. ● The elderly, women and people with normal BMI are at higher risk for air pollution. The relationship between air pollution and cerebrovascular disease has become a popular topic, yet research findings are highly heterogeneous. This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels. The integrated models of generalized additive model, land use regression model and back propagation neural network were used to evaluate the exposure concentrations. And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics, physical examination, disease information, geographic and socioeconomic status. A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018. With a 1 μg/m³ increase in the concentrations of PM_2.5, SO₂ and NO₂, the incidence risk of cerebrovascular disease increased by 1.02 (95% CI: 1.008–1.034), 1.06 (95% CI: 1.034–1.095) and 1.02 (95% CI: 1.010–1.029) respectively. Whereas CO exposure could decrease the risk, with an odds ratio of 0.38 (95% CI: 0.212–0.626). In the subgroup analysis, individuals under the age of 50 with normal BMI were at higher risk caused by PM_2.5, and SO₂ was considered more hazardous to women. Meanwhile, the protective effect of CO on women and those with normal BMI was stronger. Successful reduction of long-term exposure to PM_2.5, SO₂ and NO₂ would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.     

Investigating the impact of air pollution on AMI and COPD hospital admissions in the coastal city of Qingdao,China

• The impact of air pollution on AMI/COPD hospital admissions were examined. • Significant connection was found between air pollutants and AMI/COPD in Qingdao. • Nonlinearity exists between air pollution and AMI/COPD hospital admissions. Air pollution has been widely associated with adverse effects on the respiratory and cardiovascular systems. We investigated the relationship between acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD) and air pollution exposure in the coastal city of Qingdao, China. Air pollution in this region is characterized by inland and oceanic transportation sources in addition to local emission. We examined the influence of PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃ concentrations on hospital admissions for AMI and COPD from October 1, 2014, to September 30, 2018, in Qingdao using a Poisson generalized additive model (GAM). We found that PM_2.5, PM₁₀, NO₂, SO₂ and CO exhibited a significant short-term (lag 1 day) association with AMI in the single-pollutant model among older adults (>65 years old) and females, especially during the cold season (October to March). In contrast, only NO₂ and SO₂ had clear cumulative lag associations with COPD admission for females and those over 65 years old at lag 01 and lag 03, respectively. In the two-pollutant model, the exposure-response relationship fitted by the two-pollutant model did not change significantly. Our findings indicated that there is an inflection point between the concentration of certain air pollutants and the hospital admissions of AMI and COPD even under the linear assumption, indicative of the benefits of reducing air pollution vary with pollution levels. This study has important implications for the development of policy for air pollution control in Qingdao and the public health benefits of reducing air pollution levels.     

Source apportionment of PM2.5 in Tangshan,China—Hybrid approaches for primary and secondary species apportionment

The new hybrid approaches for the source apportionment of PM_2.5 were proposed. The hybrid approach can be used for source apportionment of secondary species. The metallurgy industry was the biggest contribution source to PM_2.5 of Tangshan. In winter, the contribution from the coal-fired boilers was the largest one. The objective of this paper is to propose a hybrid approach for the source apportionment of primary and secondary species of PM_2.5 in the city of Tangshan. The receptor-based PMF (Positive Matrix Factorization) is integrated with the emission inventory (EI) to form the first hybrid method for the source apportionment of the primary species. The hybrid CAMx-PSAT-CP (Comprehensive Air Quality Model with Extensions – Particulate Source Apportionment Technology – Chemical Profile) approach is then proposed and used for the source apportionment of the secondary species. The PM_2.5 sources identified for Tangshan included the soil dust, the metallurgical industry, power plants, coal-fired boilers, vehicles, cement production, and other sources. It is indicated that the PM_2.5 pollution is a regional issue. Among all the identified sources, the metallurgy industry was the biggest contribution source to PM_2.5, followed by coal-fired boilers, vehicles and soil dust. The other-source category plays a crucial role for PM_2.5, particularly for the formation of secondary species and aerosols, and these other sources include non-specified sources such as agricultural activities, biomass combustion, residential emissions, etc. The source apportionment results could help the local authorities make sound policies and regulations to better protect the citizens from the local and regional PM_2.5 pollution. The study also highlights the strength of utilizing the proposed hybrid approaches in the identification of PM_2.5 sources. The techniques used in this study show considerable promise for further application to other regions as well as to identify other source categories of PM_2.5.     

乌鲁木齐市米东区大气降水的化学特征及来源分析

为研究乌鲁木齐市米东区大气降水中的化学组分特征及来源,对2017-2019年降水中主要离子浓度及来源进行了分析.研究结果显示,米东区2017-2019年降水的雨量加权pH年均值为7.95,雨量加权平均电导率年均值为16.15 mS·m-1,雨量加权平均总离子浓度为72.75-95.89 μeq·L-1,年均浓度为81....     

嘉善冬季PM2.5化学组分特征及来源分析

为研究嘉兴地区嘉善冬季污染时段和清洁时段PM_2.5化学组分特征,结合气象数据对2019年1月嘉兴市嘉善县善西超级站在线自动监测PM_2.5及化学组分数据、气态污染物(NO₂和SO₂)进行了分析.结果表明,2019年1月嘉善善西超级站污染时段PM_2.5浓度(97.18μg·m^-3)为清洁时段(36.77μg·m^-3)的2.6倍.污染时段水溶性离子浓度(41.58μg·m^-3)较清洁时段(19.82μg·m^-3)高21.76μg·m^-3,但占比有所降低,含碳组分比例增加.OC;EC比值为3.93,可能受到燃煤及机动车排放的共同影响.低风速及高湿有利于NO₂和SO₂等气态污染物进行二次转化,污染时段硫转化率和氮转化率均比清洁时段高,分别增高7.93%和54.11%,说明NOx向硝酸盐二次转化较为明显,导致颗粒物浓度升高.聚类分析结果显示67.34%气流来自北方,且相应的气流轨迹上污染物浓度比周边高,说明污染物存在一定的长距离输送.结合风玫瑰图可以看出,污染主要为本地及其周边的输送,污染物的长距离输送在短时会使污染浓度突增.因此,在重点关注本地及周边污染的同时,偏北气流下的污染物区域输送不可忽视.     

Physical and chemical processes of wintertime secondary nitrate aerosol formation

The UCD/CIT model was modified to include a process analysis (PA) scheme for gas and particulate matter (PM) to study the formation of secondary nitrate aerosol during a stagnant wintertime air pollution episode during the California Regional PM_2.5/PM₁₀ Air Quality Study (CRPAQS) where detailed measurements of PM components are available at a few sites. Secondary nitrate is formed in the urban areas from near the ground to a few hundred meters above the surface during the day with a maximum modeled net increase rate of 4 μg·m^-3·d^-1 during the study episode. The secondary nitrate formation rate in rural areas is lower due to lower NO₂. In the afternoon hours, near-surface temperature can be high enough to evaporate the particulate nitrate. In the nighttime hours, both the gas phase N₂O₅ reactions with water vapor and the N₂O₅ heterogeneous reactions with particle-bound water are important for secondary nitrate formation. The N₂O₅ reactions are most import near the surface to a few hundred meters above surface with a maximum modeled net secondary nitrate increase rate of 1 μg·m^-3·d^-1 and are more significant in the rural areas where the O₃ concentrations are high at night. In general, vertical transport during the day moves the nitrate formed near the surface to higher elevations. During the stagnant days, process analysis indicates that the nitrate concentration in the upper air builds up and leads to a net downward flux of nitrate through vertical diffusion and a rapid increase of surface nitrate concentration.     

δ15N-stable isotope analysis of NHx: An overview on analytical measurements,source sampling and its source apportionment

• Challenges in sampling of NH₃ sources for d¹⁵N analysis are highlighted. • Uncertainties in the isotope-based source apportionment of NH₃ and NH₄⁺ are outlined. • Characterizing dynamic isotopic fractionation may reduce uncertainties of NH_x science. Agricultural sources and non-agricultural emissions contribute to gaseous ammonia (NH₃) that plays a vital role in severe haze formation. Qualitative and quantitative contributions of these sources to ambient PM_2.5 (particulate matter with an aerodynamic equivalent diameter below 2.5 µm) concentrations remains uncertain. Stable nitrogen isotopic composition (δ¹⁵N) of NH₃ and NH₄⁺ (δ¹⁵N(NH₃) and δ¹⁵N(NH₄⁺), respectively) can yield valuable information about its sources and associated processes. This review provides an overview of the recent progress in analytical techniques for δ¹⁵N(NH₃) and δ¹⁵N(NH₄⁺) measurement, sampling of atmospheric NH₃ and NH₄⁺ in the ambient air and their sources signature (e.g., agricultural vs. fossil fuel), and isotope-based source apportionment of NH₃ in urban atmosphere. This study highlights that collecting sample that are fully representative of emission sources remains a challenge in fingerprinting δ¹⁵N(NH₃) values of NH₃ emission sources. Furthermore, isotopic fractionation during NH₃ gas-to-particle conversion under varying ambient field conditions (e.g., relative humidity, particle pH, temperature) remains unclear, which indicates more field and laboratory studies to validate theoretically predicted isotopic fractionation are required. Thus, this study concludes that lack of refined δ¹⁵N(NH₃) fingerprints and full understanding of isotopic fractionation during aerosol formation in a laboratory and field conditions is a limitation for isotope-based source apportionment of NH₃. More experimental work (in chamber studies) and theoretical estimations in combinations of field verification are necessary in characterizing isotopic fractionation under various environmental and atmospheric neutralization conditions, which would help to better interpret isotopic data and our understanding on NH_x (NH₃ + NH₄⁺) dynamics in the atmosphere.     

Mass concentrations and temporal profiles of PM10, PM2.5 and PM1 near major urban roads in Beijing

Mass concentrations of PM₁₀, PM_2.5 and PM₁ were measured near major roads in Beijing during six periods: summer and winter of 2001, winter of 2007, and periods before, during and after the 2008 Beijing Olympic Games. Since the control efforts for motor vehicles helped offset the increase of emissions from the rapid growth of vehicles, the averaged PM_2.5 concentrations at roadsides during the sampling period between 2001 and 2008 fluctuated over a relatively small range. With the implementation of temporary traffic control measures during the Olympics, a clear “V” shaped curve showing the concentrations of particulate matter and other gaseous air pollutants at roadsides over time was identified. The average concentrations of PM₁₀, PM_2.5, CO and NO decreased by 31.2%, 46.3%, 32.3% and 35.4%, respectively, from June to August; this was followed by a rebound of all air pollutants in December 2008. Daily PM₁₀ concentrations near major roads exceeded the National Ambient Air Quality Standard (Grade II) for 61.2% of the days in the non-Olympic periods, while only for 12.5% during the Olympics. The mean ratio of PM_2.5/PM₁₀ near major roads remained relatively stable at 0.55 (±0.108) on non-Olympic days. The ratio decreased to 0.48 (±0.099) during the Olympics due to a greater decline in fine particles than in coarse-mode PM. The ratios PM₁/PM_2.5 fluctuated over a wide range and were statistically different from each other during the sampling periods. The average ratios of PM₁/PM_2.5 on non-Olympic days were 0.71.     

Understand the local and regional contributions on air pollution from the view of human health impacts

• PM_2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. • Local emissions contribute more to PM_2.5-related deaths than PM_2.5 concentration. • Local controls are underestimated if only considering its impacts on concentrations. • Rural residents suffer larger impacts of regional transport than urban residents. • Reducing regional transport benefits in mitigating environmental inequality. The source-receptor matrix of PM_2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM_2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM_2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure–response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM_2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM_2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM_2.5 particularly for local residents. Contribution of regional transport to PM_2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM_2.5 pollution thus mitigating the associated environmental inequality.     

How aerosol direct effects influence the source contributions to PM2.5 concentrations over Southern Hebei,China in severe winter haze episodes

The aerosol direct effects result in a 3%–9% increase in PM_2.5 concentrations over Southern Hebei. These impacts are substantially different under different PM_2.5 loadings. Industrial and domestic contributions will be underestimated if ignoring the feedbacks. Beijing-Tianjin-Hebei area is the most air polluted region in China and the three neighborhood southern Hebei cities, Shijiazhuang, Xingtai, and Handan, are listed in the top ten polluted cities with severe PM_2.5 pollution. The objective of this paper is to evaluate the impacts of aerosol direct effects on air quality over the southern Hebei cities, as well as the impacts when considering those effects on source apportionment using three dimensional air quality models. The WRF/Chem model was applied over the East Asia and northern China at 36 and 12 km horizontal grid resolutions, respectively, for the period of January 2013, with two sets of simulations with or without aerosol-meteorology feedbacks. The source contributions of power plants, industrial, domestic, transportation, and agriculture are evaluated using the Brute-Force Method (BFM) under the two simulation configurations. Our results indicate that, although the increases in PM_2.5 concentrations due to those effects over the three southern Hebei cities are only 3%–9% on montly average, they are much more significant under high PM_2.5 loadings (~50 μg·m⁻³ when PM_2.5 concentrations are higher than 400 μg m⁻³). When considering the aerosol feedbacks, the contributions of industrial and domestic sources assessed using the BFM will obviously increase (e.g., from 30%–34% to 32%–37% for industrial), especially under high PM_2.5 loadings (e.g., from 36%–44% to 43%–47% for domestic when PM_2.5>400 μg·m⁻³). Our results imply that the aerosol direct effects should not be ignored during severe pollution episodes, especially in short-term source apportionment using the BFM.     

无机离子对左旋葡聚糖光降解的影响

左旋葡聚糖(LG)被广泛作为生物质燃烧的示踪剂.然而,近年来研究表明左旋葡聚糖在大气中不稳定而会发生光降解.此外,对于大气中含量较高的SO₄^2-、NO₃-、NO₂-无机离子对LG光解的影响罕有报到.为此,本文模拟了液相中SO₄^2-、NO₃-、NO₂-对LG光氧化行为的影响.结果表明,Na2SO₄、NaNO₃、NaNO₂条件下LG光解速率常数分别为0.208、0.182、0.165 min^-1,均低于对照组(0.266 min-1),这表明无机离子的存在会减缓LG光降解速率.此外,这3种无机离子对LG光解产物中的低分子脂肪酸分布,甲酸/乙酸(C1/C2)比率均有重要的影响.其中,SO₄^2-存在下产物中戊二酸较多、NO₃-存在下产物中甲酸较多、NO₂-存在下产物中乙酸较多;NO₂-存在下产物中的C1/C2比率小于1与一般二次源中的C1/C2比率不一致,这表明由单一反应引起的C1/C2并不总是大于1.这些结果对于我们深刻理解大气液相中的有机物转化具有重要的参考价值.     

青藏高原东缘冬季PM2.5中碳组分特征和来源解析

于2017年冬季12月13—21日在青藏高原东缘理塘地区分昼夜采集PM_2.5样品,并用DRI2001A热光碳分析仪测定了有机碳(OC)和元素碳(EC)的质量浓度,研究青藏高原PM_2.5中碳组分的化学特征及主要来源,以期为理塘地区制定污染排放政策提供参考。结果表明,2017年冬季青藏高原东缘理塘地区PM_2.5平均质量浓度为44.34μg·m^?3,OC和EC的质量浓度为12.72μg·m^?3和3.85μg·m^?3,分别占PM_2.5质量浓度的29.61%和8.96%。通过经验公式,计算得到总碳气溶胶(TCA)质量浓度为24.20μg·m^?3,占PM_2.5的54.84%,说明碳质气溶胶对青藏高原东缘理塘地区PM_2.5有着十分重要的贡献。OC和EC在白天和夜间都有较高的相关性(相关系数分别为0.74和0.91),表明OC和EC的来源基本一致,受燃烧源影响较大。其中白天的相关系数低于夜间,说明青藏高原东缘理塘地区白天碳组分来源相对复杂。昼夜浓度对比显示,青藏高原东缘理塘地区PM_2.5白天和夜间的质量浓度分别为53.88μg·m^?3和33.44μg·m^?3,OC和EC浓度白天高于夜间,表明白天人为排放相对较高。冬季观测期间,PM_2.5中二次有机碳(SOC)昼夜浓度分别为1.11μg·m^?3和3.03μg·m^?3,分别占OC质量浓度的7.09%、26.59%,表明青藏高原东缘理塘城区白天碳组分主要为一次源。利用PMF 5.0软件对理塘城区碳组分进行进一步的解析,结果显示燃煤和生物质燃烧的混合源对总碳(TC)的贡献高达47.84%,占比最高;其次是汽车尾气和柴油车尾气源,贡献率分别为28.62%和23.54%。     

天津市采暖季PM2.5组分消光特性及来源分析

为了解天津市采暖季细颗粒物组分对能见度的影响、明确消光组分来源,对天津市2017年采暖季大气PM_2.5样品进行了为期一月的连续采集,并测定水溶性离子、有机碳和元素碳的含量,通过修正IMPROVE方程研究了细颗粒物消光特性,并采用主成分分析—多元线性回归模型(PCA-MLR)对其来源进行解析,同时应用潜在源贡献因子(PSCF)和浓度权重轨迹(CWT)明确PM_2.5质量浓度的潜在污染源区域。结果表明,OC、EC以及SNA(NO3^?、NH₄⁺、SO₄^2?)的生成和积累对于能见度的下降具有重要影响,且能见度随SOR和NOR二次转化程度的升高而下降;2017年天津市采暖季日均消光系数为(294.56±262.89)Mm^?1,其中OM(34.86%)、硝酸盐(22.84%)、硫酸盐(11.59%)和EC(11.54%)为主要消光组分,硝酸盐和硫酸盐的增加对于能见度的下降起主要影响作用;根据PCA分析结果可知,天津市采暖季PM_2.5中的碳组分和水溶性离子主要来源于燃煤、生物质燃烧(68%),受扬尘(22%)和海盐(8%)的影响较小;区域传输分析结果表明天津市采暖季PM_2.5污染源潜在区域主要分布在河北中西部、河南北部、山西北部和内蒙古中部、西部。     

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit metal mine

Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM_2.5, PM₁₀, NO_x, SO₂ and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.