Local and regional contributions to PM2.5 in the Beijing 2022 Winter Olympics infrastructure areas during haze episodes

• Regional transportation contributed more than local emissions during haze episodes. • Short-range regional transportation contributed the most to the PM_2.5 in the OIAs. • Low wind speeds and low PBLHs led to higher local contributions to Beijing. The 2022 Winter Olympics is scheduled to take place in Beijing and Zhangjiakou, which were defined as OIAs (Olympic infrastructure areas) in this study. This study presents the characteristics and source apportionment of PM_2.5 in the OIAs, China. The entire region of mainland China, except for the OIAs, was divided into 9 source regions, including four regions in the BTH(Beijing-Tianjin-Hebei) region, the four provinces surrounding the BTH and the remaining areas. Using CAMx/PSAT, the contributions of the nine regions to the PM_2.5 concentration in the OIAs were simulated spatially and temporally. The simulated source apportionment results showed that the contribution of regional transportation was 48.78%, and when PM_2.5 concentration was larger than 75 μg/m³ central Hebei was the largest contributor with a contribution of 19.18%, followed by Tianjin, northern Hebei, Shanxi, Inner Mongolia, Shandong, southern Hebei, Henan and Liaoning. Furthermore, the contribution from neighboring regions of the OIAs was 47.12%, which was nearly twice that of long-range transportation. Haze episodes were analyzed, and the results presented the importance of regional transportation during severe PM_2.5 pollution periods. It was also found that they were associated with differences in pollution sources between Zhangjiakou and Beijing. Regional transportation was the main factor affecting PM_2.5 pollution in Zhangjiakou due to its low local emissions. Stagnant weather with a low planetary boundary layer height and a low wind velocity prevented the local emitted pollutants in Beijing from being transported outside, and as a result, local emissions constituted a larger contribution in Beijing.     

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.     

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.     

PM2.5 concentration declining saves health expenditure in China

● Monthly hospitalization expenses are sensitive to increases in PM_2.5 exposure. ● The increased PM_2.5 causes patients with CHD and LRI to stay longer in the hospital. ● The impact of PM_2.5 on total expenses for stroke is greater in southern China. ● Males may be more sensitive to air pollution than females. Air pollution has been a severe issue in China. Exposure to PM_2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM_2.5 pollution using monthly city-level data covering 88.5 million urban employees in 2016 and 2017. This study mainly focused on three expenditure indicators to measure the economic impact considering lower respiratory infections (LRIs), coronary heart disease (CHD), and stroke. The results show that a 10 µg/m³ increase in PM_2.5 would cause total monthly expenses of LRIs, CHD, and stroke to increase by 0.226%, 0.237%, and 0.374%, respectively. We also found that LRI, CHD, and stroke hospital admissions increased significantly by 10%, 8.42%, and 5.64%, respectively. Furthermore, the total hospital stays of LRIs, CHDs, and strokes increased by 2.49%, 2. 51%, and 1.64%, respectively. Our findings also suggest heterogeneous impacts of PM_2.5 exposures by sex and across regions, but no statistical evidence shows significant differences between the older and younger adult subgroups. Our results provide several policy implications for reducing unequal public health expenditures in overpolluted countries.     

PM2.5 over North China based on MODIS AOD and effect of meteorological elements during 2003‒2015

• The Taihang Mountains was the boundary between high and low pollution areas. • There were one high value center for PM_2.5 pollution and two low value centers. • In 2004, 2009 and after 2013, PM_2.5 concentration was relatively low. Over the past 40 years, PM_2.5 pollution in North China has become increasingly serious and progressively exposes the densely populated areas to pollutants. However, due to limited ground data, it is challenging to estimate accurate PM_2.5 exposure levels, further making it unfavorable for the prediction and prevention of PM_2.5 pollutions. This paper therefore uses the mixed effect model to estimate daily PM_2.5 concentrations of North China between 2003 and 2015 with ground observation data and MODIS AOD satellite data. The tempo-spatial characteristics of PM_2.5 and the influence of meteorological elements on PM_2.5 is discussed with EOF and canonical correlation analysis respectively. Results show that overall R² is 0.36 and the root mean squared predicted error was 30.1 μg/m³ for the model prediction. Our time series analysis showed that, the Taihang Mountains acted as a boundary between the high and low pollution areas in North China; while the northern part of Henan Province, the southern part of Hebei Province and the western part of Shandong Province were the most polluted areas. Although, in 2004, 2009 and dates after 2013, PM_2.5 concentrations were relatively low. Meteorological/topography conditions, that include high surface humidity of area in the range of 34°‒40°N and 119°‒124°E, relatively low boundary layer heights, and southerly and easterly winds from the east and north area were common factors attributed to haze in the most polluted area. Overall, the spatial distribution of increasingly concentrated PM_2.5 pollution in North China are consistent with the local emission level, unfavorable meteorological conditions and topographic changes.     

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.     

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.     

Temporal variation of PM2.5-associated health effects in Shijiazhuang,Hebei

•Annual mean PM_2.5 in Shijiazhuang were 87, 95, and 82 µg/m³ in 2015–2017. •Health risk of cardiovascular system was higher than respiratory system. •Premature mortality attributed to PM_2.5 was 5088 people in 2017. •ΔMort and YLL reduced by 84.2% and 84.6% when PM_2.5 reduced to 10 µg/m³. •Health risks due to PM_2.5 were severe in Shijiazhuang in 2015–2017. Shijiazhuang is one of the cities in the North China Plain. In recent decades, this city has experienced high levels of fine particulate matter (PM_2.5), which have potentially significant effects on human health. In this study, the health effects of PM_2.5 exposure in Shijiazhuang were estimated by applying an integrated exposure-response model. Premature mortality, years of life lost (YLL), and the mortality benefits linked to reduced levels of PM_2.5 were quantified for the period 2015–2017. In 2015, 2016, and 2017, cerebrovascular diseases caused the highest premature mortality (2432, 2449, and 2483, respectively), followed by ischemic heart diseases (1391, 1479, and 1493, respectively), lung cancer (639,660, and 639, respectively), and chronic obstructive pulmonary diseases (533, 519, and 473, respectively). Notably, the total number of premature deaths caused by PM_2.5 exposure in Shijiazhuang in 2015, 2016, and 2017 were 4994, 5107, and 5088, respectively. Moreover, the YLL in the same years were 47001, 47880 and 47381, respectively. Interestingly, the YLL per 1000 females was lower than that per 1000 males. Finally, we noted that premature mortality and YLL decreased by 84.2% and 84.6% when the PM_2.5 levels diminished to 10 µg/m³. Overall, the results of this study improve our understanding of how high PM_2.5 concentrations affect human health and suggest the application of more stringent measures in Shijiazhuang to alleviate the associated health risks.     

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.     

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%。     

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.     

Seasonal variations of transport pathways and potential sources of PM2.5 in Chengdu,China (2012–2013)

PM_2.5 in Chengdu showed clear seasonal and diurnal variation. 5, 5, 5 and 3 mean clusters are generated in spring, summer, autumn, and winter. Short-distance air masses are important pathways in Chengdu. Emissions within the Sichuan Basin contribute significantly to PM_2.5 pollution. Long-range transport from Southern Xinjiang is a dust invasion path to Chengdu. Seasonal pattern of transport pathways and potential sources of PM_2.5 in Chengdu during 2012–2013 were investigated based on hourly PM_2.5 data, backward trajectories, clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) method. The annual hourly mean PM_2.5 concentration in Chengdu was 97.4 mg·m^–3. 5, 5, 5 and 3 mean clusters were generated in four seasons, respectively. Short-distance air masses, which travelled within the Sichuan Basin with no specific source direction and relatively high PM_2.5 loadings (>80 mg·m^–3) appeared as important pathways in all seasons. These short pathways indicated that emissions from both local and surrounding regions of Chengdu contributed significantly to PM_2.5 pollution. The cities in southern Chengdu were major potential sources with PSCF>0.6 and CWT>90 mg·m^–3. The northeastern pathway prevailed throughout the year with higher frequency in autumn and winter and lower frequency in spring and summer. In spring, long-range transport from southern Xinjiang was a representative dust invasion path to Chengdu, and the CWT values along the path were 30-60 mg·m^–3. Long-range transport was also observed in autumn from southeastern Xinjiang along a northwesterly pathway, and in winter from the Tibetan Plateau along a westerly pathway. In summer, the potential source regions of Chengdu were smaller than those in other seasons, and no long-range transport pathway was observed. Results of PSCF and CWT indicated that regions in Qinghai and Tibet contributed to PM_2.5 pollution in Chengdu as well, and their CWT values increased to above 30 mg·m^-3 in winter.     

Diverse bacterial populations of PM2.5 in urban and suburb Shanghai,China

• Urban aerosols harbour diverse bacterial communities in Shanghai. • The functional groups were associated with nitrogen, carbon, and sulfur cycling. • Temperature, SO₂, and wind speed were key drivers for the bacterial community. Airborne bacteria play key roles in terrestrial and marine ecosystems and human health, yet our understanding of bacterial communities and their response to the environmental variables lags significantly behind that of other components of PM_2.5. Here, atmospheric fine particles obtained from urban and suburb Shanghai were analyzed by using the qPCR and Illumina Miseq sequencing. The bacteria with an average concentration of 2.12 × 10³ cells/m³, were dominated by Sphingomonas, Curvibacter, Acinetobacter, Bradyrhizobium, Methylobacterium, Halomonas, Aliihoeflea, and Phyllobacterium, which were related to the nitrogen, carbon, sulfur cycling and human health risk. Our results provide a global survey of bacterial community across urban, suburb, and high-altitude sites. In Shanghai (China), urban PM_2.5 harbour more diverse and dynamic bacterial populations than that in the suburb. The structural equation model explained about 27%, 41%, and 20%–78% of the variance found in bacteria diversity, concentration, and discrepant genera among urban and suburb sites. This work furthered the knowledge of diverse bacteria in a coastal Megacity in the Yangtze river delta and emphasized the potential impact of environmental variables on bacterial community structure.     

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....     

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。     

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.     

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.     

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.     

南京秋季大气PM2.5中类腐殖质的光学性质与来源分析

类腐殖质(humic-like substances, HULIS)是水溶性有机碳(WSOC)中具有吸光特性的重要组分,对空气质量、气候变化和人体健康均有重要影响.尽管目前对HULIS的研究很多,但不同方法分离机理不同,对于HULIS的分离与测定仍然缺乏统一的标准,针对HULIS分离方法的研究很少.固相萃取法(solid phase extraction, SPE)因其操作简单、分离效果较好而被广泛应用,但对于低浓度样品仍存在检出限较高、回收率较低的问题,且很少有人关注提纯过程中流程空白所包含的含碳组分及其吸光能力.本研究通过调整活化溶液(0.01 mol·L^-1 HCl溶液+甲醇+2%NH₃H₂O/MeOH)与洗脱溶液(2%NH₃H₂O/MeOH)用量的比例对提纯方法进行优化.结果表明,应用优化后的方法对流程空白进行测量时,检出限(MDL)降低到0.035 mg·L^-1以下,精密度RSD <5.41%(n=20),标准品回收率达到95%,在保证回收率的情况下减少了流程空白,提高了样品的精密度,使测定浓度较低的HULIS含量成为可能.为了探究生物质燃烧期间含碳组分的光学特性和来源特征,本研究对2017年10月6日至11月9日南京北郊秋季大气气溶胶样品进行采集.采样期间PM_2.5的浓度为(87.9±43.7)μg·m^-3,WSOC和类腐殖质碳(HULIS-C)的浓度分别为(4.2±2.3)μg·m^-3和(3.6±2.0)μg·m^-3,HULIS-C占WSOC的比例为47.3%,是WSOC中的重要组成部分.本研究还对HULIS在330—400 nm波段的吸光进行测定,使用Angstrom指数(absorption angstrom exponent,AAE)进行表征,得到采样期间AAE的值为2—7,说明HULIS污染主要来自二次转化.后向轨迹结果表明,重污染期间污染物来源为本地生物质燃烧和区域或者长距离气团的输送.     

Collaborative control of fine particles and ozone required in China for health benefit

● Increased DAAO offsets 3/4 of the decrease of DAAP in 2013–2020. ● DAAO increases are mainly due to O₃ concentration increase and population aging. ● Health benefit from PM_2.5 reduction after 2017 is larger than that before 2017. ● Reducing PM_2.5 concentration by 1% results in 0.6% reduction of DAAP. ● Reducing O₃ concentration by 1% results in 2% reduction of DAAO. PM_2.5 concentration declined significantly nationwide, while O₃ concentration increased in most regions in China in 2013–2020. Recent evidences proved that peak season O₃ is related to increased death risk from non-accidental and respiratory diseases. Based on these new evidences, we estimate excess deaths associated with long-term exposure to ambient PM_2.5 and O₃ in China following the counterfactual analytic framework from Global Burden Disease. Excess deaths from non-accidental diseases associated with long-term exposure to ambient O₃ in China reaches to 579 (95% confidential interval (CI): 93, 990) thousand in 2020, which has been significantly underestimated in previous studies. In addition, the increased excess deaths associated with long-term O₃ exposure (234 (95% CI: 177, 282) thousand) in 2013–2020 offset three quarters of the avoided excess deaths (302 (95% CI: 244, 366) thousand) mainly due to PM_2.5 exposure reduction. In key regions (the North China Plain, the Yangtze River Delta and the Fen-Wei Plain), the former is even larger than the latter, particularly in 2017–2020. Health benefit of PM_2.5 concentration reduction offsets the adverse effects of population growth and aging on excess deaths attributed to PM_2.5 exposure. Increase of excess deaths associated with O₃ exposure is mainly due to the strong increase of O₃ concentration, followed by population aging. Considering the faster population aging process in the future, collaborative control, and faster reduction of PM_2.5 and O₃ are needed to reduce the associated excess deaths.