A monitoring-modeling approach to SO42 − and NO3− secondary conversion ratio estimation during haze periods in Beijing, China

SO_4~(2-) and NO_3~- are important chemical components of fine particulate matter(PM_(2.5)),especially during haze periods.This study selected two haze episodes in Beijing,China with similar meteorological conditions.A monitoring-modeling approach was developed to estimate the secondary conversion ratios of sulfur and nitrogen based on monitored and simulated concentrations.Measurements showed that in Episode 1(24th–25th October,2014),the concentrations(proportions)of SO_4~(2-) and NO_3~- reached 35.1μg/m~3(14.9%) and 55.0μg/m~3(22.9%),while they reached 14.4μg/m~3(9.3%) and 59.1μg/m~3(38.1%)in Episode 2(26th–27th October,2017).A modeling system was applied to apportion Beijing's SO_4~(2-) and NO_3~- in primary and secondary SO_4~(2-)/NO_3~- emitted from local and regional sources.Thus,secondary conversion contributions considering the local and regional level were defined.The former primarily focused on Beijing atmospheric oxidation ability and the latter mainly considered the existence form of Beijing SO_4~(2-)/NO_3~- under the regional transport impacts.Finally,secondary oxidation ratios were estimated through combining secondary conversion contribution coefficients for simulated and monitored concentrations.At regional level,sulfur oxidation ratios in polluted(clean)days during two sampling periods were0.57–0.72(0.07–0.52)and 0.74–0.80(0.08–0.61),nitrogen oxidation ratios were 0.20–0.29(0.05–0.15)and 0.34–0.38(0.02–0.29),indicating that atmospheric oxidation was enhanced when considering regional transport through 2014–2017.At the local level,sulfur oxidation ratios were 0.66–0.71(0.04–0.48)in haze(clean)days,while nitrogen oxidation ratios were0.16–0.29(0.02–0.16).The atmospheric oxidation ability markedly increased in PM_(2.5)pollution days,but changed only slightly between the two periods.     

穗港晴沙两重天——2010年3月17—23日珠三角典型灰霾过程分析

随着经济规模迅速扩大和城市化进程加快,大气气溶胶污染日趋严重,由细粒子气溶胶造成的能见度恶化事件越来越多,这些人类活动排放的污染物,可形成灰霾天气致使能见度下降.2010年3月17-23日,在珠三角地区发生了一次典型灰霾天气过程,同期20日左右,中亚、蒙古国与我国北方发生了当年沙尘天气影响范围最广的一次强沙尘暴过程,冷...     

Chemical characterization of size-resolved aerosols in four seasons and hazy days in the megacity Beijing of China

Size-resolved aerosol samples were collected by MOUDI in four seasons in 2007 in Beijing. The PM10 and PM1.8mass concentrations were 166.0 ± 120.5 and 91.6 ± 69.7 μg/m~3, respectively,throughout the measurement, with seasonal variation: nearly two times higher in autumn than in summer and spring. Serious fine particle pollution occurred in winter with the PM1.8/PM10 ratio of 0.63, which was higher than other seasons. The size distribution of PM showed obvious seasonal and diurnal variation, with a smaller fine mode peak in spring and in the daytime. OM(organic matter = 1.6 × OC(organic carbon)) and SIA(secondary inorganic aerosol) were major components of fine particles, while OM, SIA and Ca_2+were major components in coarse particles. Moreover, secondary components, mainly SOA(secondary organic aerosol) and SIA,accounted for 46%–96% of each size bin in fine particles, which meant that secondary pollution existed all year. Sulfates and nitrates, primarily in the form of(NH_4)_2SO_4, NH_4NO_3, Ca SO_4, Na_2SO_4 and K_2SO_4, calculated by the model ISORROPIA II, were major components of the solid phase in fine particles. The PM concentration and size distribution were similar in the four seasons on non-haze days, while large differences occurred on haze days, which indicated seasonal variation of PM concentration and size distribution were dominated by haze days. The SIA concentrations and fractions of nearly all size bins were higher on haze days than on non-haze days, which was attributed to heterogeneous aqueous reactions on haze days in the four seasons.     

Role of secondary aerosols in haze formation in summer in the Megacity Beijing

A field experiment from 18 August to 8 September 2006 in Beijing, China, was carried out. A hazy day was defined as visibility 10 km and RH(relative humidity) 90%. Four haze episodes, which accounted for ~ 60% of the time during the whole campaign, were characterized by increases of SNA(sulfate, nitrate, and ammonium) and SOA(secondary organic aerosol) concentrations. The average values with standard deviation of SO2-+4, NO-3, NH4 and SOA were 49.8(± 31.6), 31.4(±22.3), 25.8(±16.6) and 8.9(±4.1) μg/m3, respectively, during the haze episodes, which were 4.3, 3.4, 4.1, and 1.7 times those in the non-haze days. The SO2-4,NO-3, NH+4, and SOA accounted for 15.8%, 8.8%, 7.3%, and 6.0% of the total mass concentration of PM10 during the non-haze days. The respective contributions of SNA species to PM10 rose to about27.2%, 15.9%, and 13.9% during the haze days, while the contributions of SOA maintained the same level with a slight decrease to about 4.9%. The observed mass concentrations of SNA and SOA increased with the increase of PM10 mass concentration, however, the rate of increase of SNA was much faster than that of the SOA. The SOR(sulfur oxidation ratio) and NOR(nitrogen oxidation ratio) increased from non-haze days to hazy days, and increased with the increase of RH. High concentrations of aerosols and water vapor favored the conversion of SO2 to SO2-4and NO2 to NO-3, which accelerated the accumulation of the aerosols and resulted in the formation of haze in Beijing.     

北京市地表水污染原因分析与防治对策

分析了北京市地表水污染的主要原因,提出了解决措施,对合理利用紧缺的水资源问题,有一定的指导意义。北京地区严重缺水,且地表水污染严重。主要原因有以下4方面:水资源量逐年减少,生活污染源影响严重,城市中心区污水截流河道地表雨水径流污染逐年凸显,农业面源污染增加。提出如下控制措施:保证地表水生态流量,建设双水源(清水和再生水)供水系统;科学核算地表水环境容量,把污染物排放总量控制与改善水环境质量紧密结合起来,是改善地表水环境质量的重要措施;加强城市地表径流污染研究与控制,尤其是初期雨水污染控制;引入循环经济,建设生态农业,改善养殖方式,控制农村面源污染。     

基于三次指数平滑模型的雾霾天气分析与预测

通过建立三次指数平滑模型,分析2002~2012年我国二氧化硫和烟尘的排放量以及每年在环境污染治理方面的投资总额等指标,得出未来3年内我国雾霾天气仍会频发的结论,并究其原因进行了分析。     

成都市冬季3次灰霾污染过程特征及成因分析

基于成都市大气环境超级观测站气态污染物和PM_2.5中组分在线监测数据,对2019~2020年成都市3次灰霾污染过程气象要素和组分特征进行分析,采用CMB模型模拟获得研究期间PM_2.5污染来源及变化趋势,剖析各污染过程成因.结果表明：① 3次污染过程均发生在相对湿度和温度持续上升,风速和边界层高度持续降低的不利气象条件下,日均相对湿度均大于70%,日均温度均大于8℃,日均风速均低于0.8 m ·s^-1,日均边界层高度均低于650 m;② 3次污染过程中主要组分均为NO₃^-、OC、NH₄⁺和SO₄^2-,其中NO₃^-质量浓度和占比污染时段较清洁时段增长倍数均高于其他组分,分别增加了1.47~2.09倍和0.22~0.35倍,NO₃^-是成都市冬季PM_2.5污染的关键组分;③ 3次污染过程SOR均值为0.40,NOR均值为0.27,SO₂和NO_x的二次转化程度较高,SO₂向SO₄^2-转化以夜间非均相氧化反应为主,NO_x向NO₃^-转化以非均相水解反应为主;④ 3次过程变化特征略有不同,过程Ⅰ呈现出明显的二次硝酸盐主导的特征,过程Ⅱ PM_2.5浓度上升过程中主要受燃煤排放影响,PM_2.5浓度高值时段主要受NO₃^-影响,过程Ⅲ总体仍为二次硝酸盐主导的特征,但部分污染时段化石燃料燃烧源排放有所增加;⑤二次硝酸盐、二次硫酸盐、机动车和燃煤源为研究期间主要污染来源,PM_2.5浓度与二次硝酸盐贡献率正相关,与扬尘源贡献率负相关.     

火电烟气脱硫效率低的常见原因分析及对策

随着最严环保标准的出台及监管力度加大，对脱硫等环保设施的可靠性提出了更高要求。针对当前脱硫系统关键指标-脱硫效率，系统剖析了脱硫输入、运行参数、关键设备及仪表等诸方面影响脱硫效率的常见原因，并提出了相应的对策。     

喀斯特石漠化及其景观生态学研究展望

喀斯特石漠化是广泛分布于我国西南喀斯特地区的一种生态灾害,近30年来其扩展速度明显加快,严重制约了我国西南地区的经济发展和生态质量的提高。首先从概念、成因及防治等方面探讨了目前喀斯特石漠化的研究现状,并指出石漠化研究中的不足,主要表现为研究内容较片面,缺乏定量研究,标准不统一和缺乏景观水平上的研究。景观生态学有其特有的理论优势和方法体系,若利用景观生态学的理论和研究方法来研究石漠化,可以解决目前石漠化研究中的某些相关问题。最后,在此基础上,从景观生态学的角度出发,展望了喀斯特石漠化未来研究的4个方向,即景观格局变化、景观异质性及其分区、石漠化过程空间动态模拟和生物多样性.     

伊逊河流域总磷污染来源解析

2017—2018年TP成为滦河一级支流伊逊河流域的主要污染因子,部分国控断面水质主要以GB 3838—2002《地表水环境质量标准》Ⅳ类、Ⅴ类为主.为开展伊逊河TP污染定量识别研究,在2017年和2018年伊逊河流域水体TP污染时空特征分析的基础上,从流域磷铁矿工业污染、城镇生活污水、雨水径流、河道内源释放以及农业非点源等方面开展TP污染研究.结果表明:①伊逊河流域上游至下游TP污染程度呈加剧恶化趋势,上游唐三营控制单元污染较轻,下游李台控制单元TP污染最重;丰水期TP污染较重,枯/平水期污染较轻;从年度看,2017年TP污染严重,2018年年均ρ（TP）下降了50.00%.②2017年、2018年伊逊河流域TP污染来源差异显著,2017年磷输入主要来自于磷铁矿工业污染,占比为33.46%;选矿企业整改后,2018年磷输入主要来源变为畜禽养殖和城镇生活污染,二者占比合计为59.91%.针对伊逊河流域TP污染特征,提出伊逊河流域TP污染控制建议:加强选矿企业环境监管,进一步完善监管体系;加强流域水土流失治理,实施矿山披绿;大力实施绿色农业工程,加强畜禽养殖布局优化.