1971-2010年河南省夏季高温日数的变化趋势分析

基于河南省109个气象站1971-2010年夏季(6-8月)逐日最高气温和平均气温资料,采用气候统计学分析方法,分析了近40年河南省夏季≥35℃、≥38℃和≥40℃高温日数的时空特征及可能的变化趋势.结果表明:1971-2010年河南省夏季3个等级高温日数在空间上呈现出豫西北高海拔和豫东南低海拔地区较多,其它地区较少的分布特征,高值中心位于豫西地区的偃师附近,在时间上无显著的线性变化趋势,但是在年代间呈现出“多-少-多”的变化特征,最近10年夏季高温日数最多；从各台站趋势变化的空间分布看,豫西北海拔较高地区台站呈增加趋势的较多,豫东和豫西南台站呈减少趋势的较多.夏季平均气温和≥35 ℃(r =0.58,n=4360)、≥38℃(r=0.39,n=4360)以及≥40℃(r=0.27,n=4360)高温日数均呈显著正相关.在全球气候变暖背景下,未来河南省高温日数将可能进一步增加,特别是≥35℃的高温日数.     

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.     

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.     

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。     

2013年1月邯郸市严重霾天气的污染特征分析

利用河北工程大学大气环境监测站点的PM₁₀、PM_2.5、SO₂和NO_x在线监测数据,并结合能见度、湿度数据,对邯郸市2012年12月1日到2013年1月31日的大气污染状况进行分析,特别是2013年1月持续发生的霾天气,以探讨严重霾污染的过程特征.结果表明,2013年1月,SO₂与NO_x的平均浓度分别为225.3 μg·m^-3和217.8 μg·m^-3,PM₁₀和PM_2.5的平均浓度分别为328.5 μg·m^-3和229.4 μg·m^-3,均超过新颁布的环境空气质量标准,是2012年12月平均浓度的1.4~3.5倍.重污染过程分析结果显示,污染峰值附近几天内PM₁₀、PM_2.5的时均浓度变化无明显规律.累积阶段的PM_2.5/PM₁₀在0.42~0.52之间,峰值前后上升并超过0.70,扩散阶段PM_2.5/PM₁₀降到0.70以下,且呈波动式变化.当PM_2.5/PM₁₀小于0.40时,能见度基本位于2~18 km之间;当PM_2.5/PM₁₀在0.40~0.60之间时,能见度在0.7~8 km之间;当PM_2.5/PM₁₀大于0.60时,能见度分布于2 km以下.     

东北地区玉米低温冷害综合指标研究

在以往对低温冷害指标研究的基础上，将低温冷害成分不同的发育阶段进行分析，结合发育期日数和初霜日研究等，讨论分析了东北地区玉米的低温冷害问题，提出一个玉米低温冷害综合指标。该指标生物学和农学意义明确，计算较为方便，便于在预报上的应用。     

灰霾天气期间南京气溶胶的化学组成及光学特性研究

利用2013年6月—12月灰霾天气期间南京城郊气溶胶采样结果,研究气溶胶中水溶性离子的特征和相关性;结合同期城区的大气成分逐时观测资料,分析黑碳的日变化及其与气态污染物的关系;运用光学参量计算模型(OPAC)和辐射传输模型(TUV)研究气溶胶的光学特性及辐射强迫。结果表明:发生灰霾天气时南京城郊主要大气污染物是细颗粒,其中SO2-4与NO-3是最主要的水溶性无机盐离子,NO-3/SO2-4质量比较高,呈现硫酸盐和硝酸盐混合型污染特征。黑碳浓度具有明显的日变化特征,呈双峰型结构。灰霾期间硫酸盐气溶胶在大气层顶和地面造成的平均辐射强迫分别为-10.6 W/m2和-10.8 W/m2,黑碳气溶胶在正午大气层顶和地面造成的平均辐射强迫分别为9.12 W/m2和-29.77 W/m2。     

近50 a长江流域暴雨日数时空变化分析

利用1961~2010年长江流域逐日降水资料和DEM数据,结合Mann-Kendall趋势法、变差系数法以及GIS空间分析等方法,分析了近50 a长江流域年均暴雨日数时空变化特征。结果表明:长江流域年均暴雨日数基本呈自东向西递减的规律,且随着海拔升高,年均暴雨日数逐渐减少,两者呈显著负相关关系;长江流域上游高原气候影响区年均暴雨日数小于1 d;而中上游中亚热带湿润气候影响区大于2 d;随着纬度的增加,暴雨开始时间推迟,结束时间提前,持续时间减少;年暴雨日数的变差系数与年均暴雨日数满足幂指数关系,相关系数达0.97,为显著相关。表现为年均暴雨日数大(小)的地方,变差系数小(大);除长江中下游中部和四川盆地及其周边地区年暴雨日数为减少趋势外,其它地方均表现为不同程度的增加趋势。鄱阳湖水系、四川(雅安市、峨眉山市、万源市)、湖南(安化县、南岳区)、湖北(洪湖市、英山县)年暴雨日数多且变差系数小,洪水、泥石流等灾害压力巨大;为有关部门了解长江流域洪水等灾害的发生机制、提高灾害预测预报能力、制定防灾减灾政策等提供科学依据。     

阳泉市秋冬季PM2.5化学组分及来源分析

采集了阳泉市城区2017年10月15日～2018年1月23日PM_(2.5)样品,分析了优良天和污染天PM_(2.5)及其化学组分特征,并利用富集因子分析法(EF)和正定矩阵因子分析法(PMF)对PM_(2.5)进行来源分析.结果表明,采样期间污染天二次无机离子(SO_4~(2-)、 NO~-_3和NH~+_4)在PM_(2.5)中的比例为23.83%,是优良天的2.43倍,污染天二次无机污染严重,污染天人为源相关的元素Cd、 Sb、 Sn、 Cu、 Pb、 Zn和As富集程度大于优良天;主要的污染源对PM_(2.5)的贡献分别是燃煤29.26%、扬尘23.83%、机动车19.34%、二次源16.01%和工业源11.57%,其中,污染天机动车排放对PM_(2.5)的贡献20.57%,高于优良天时17.82%,而燃煤源的贡献23.04%明显低于优良天时33.75%,静稳天气时机动车排放对PM_(2.5)贡献较优良天上升,燃煤源对PM_(2.5)贡献有下降.因此,阳泉市在秋冬季应加强对燃煤、扬尘源的控制,同时进一步加强对机动车的控制,以减少污染期间机动车的贡献.     

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.