Temporal variations of C2 concentration near land surface and its response to meteorological variables in Heihe River Basin, northwest China

Atmospheric CO2 concentration （CC） near land surface and meteorological variables have been measured at four sites, named Yeniugou （alpine meadow and permafrost）, Xishui （mountainous forest）, Linze （oasis edge） and Ejina （lower desert）, respectively, in Heihe River Basin, northwest China. The results showed that, the half hourly CC at night was larger than in daytime, and the daily averaged CC was the largest in winter. The averaged CC of 932 d at the Linze was about 418 ppm, was about 366 ppm in the 762 d at the Ejina. In the same period from September 23 to November 9, 2004, the averaged CC was about 625,334, 436 and 353 ppm, at Yeniugou, Xishui, Linze and Ejina, respectively. The linear relationship between daily averaged CC and air temperature T was negative, between CC and relative humidity （RH） was positive. The linear CC-atmospheric pressure （A P） relationship was negative at the Linze and Yeniugou, was positive at the Ejina. The relationship between CC and global radiation R was exponent, and soil temperature Ts was negative linear, and soil water content was complex. The correlation between CC and wind speed was not existent. Using meteorological variables together to simulate CC, could give good results.     

亚热带红壤区湿地松生长与耗水耦合关系研究

采用热扩散式探针(TDP)对湿地松(Pinus elliottii)树干液流密度及其周围环境因子进行长期同步测定,同时辅以树干解析、枝条解析等树木生长量调查方法,以期探索不同尺度上湿地松水分耗失与碳蓄积特征。结果表明,液流密度与冠层温度、相对湿度、光合有效辐射总量都呈显著的线性相关关系。液流密度与上述3个因子的多元线性回归方程和回归系数的相关性检验均达极显著水平。湿地松日均耗水量与边材面积间线性相关性显著。处于低龄期的湿地松,边材面积与胸径可用二次函数很好地拟合。根据2004年湿地松树干液流观测结果和生物量调查结果,推算出湿地松在生长过程中每形成1.773 1g干物质需要消耗约1kg水分。文末还根据生物量数据推算了树木生长过程中的耗水量。     

2001~2019年气象条件对江苏省PM2.5分布的影响

利用区域在线空气质量模式WRF-Chem模拟研究了2001～2019年气象条件对江苏省PM_2.5浓度分布的影响.在排放源不变的情况下,气象条件引起的江苏省PM_2.5年均浓度的最强正、负异常分别出现在2008和2001年,它们的异常值相对于多年平均值分别占比10.5%和-14.3%,表明气象条件对PM_2.5浓度年际变化有明显影响.经验正交函数分解的结果表明,气象条件对江苏省PM_2.5浓度的空间分布的影响具有一致性.边界层高度、温度、相对湿度、风速和降水整体上都与江苏省PM_2.5浓度呈现显著负相关关系.以上气象因子所构建的线性回归方程能较好地描述PM_2.5浓度和气象条件之间的关系,其拟合值与模拟值相关性为0.73,通过了99%的信度水平检验.     

主成分和回归分析方法在大气臭氧预报的应用——以北京夏季为例

利用北京市区两个典型观测站的大气臭氧(O3)及前体物浓度观测资料和气象要素观测数据,分析了影响大气O3浓度各要素的相关性,并采用主成分分析和逐步回归方法构造大气O3浓度统计预报方程.结果表明,大气O3与前体物一氧化氮(NO)、二氧化氮(NO2)和气象要素呈现较好相关性;发现由于变量间共线性问题,逐步回归方法不能给出可接受的回归方程,而采用主成分分析和逐步回归方法相结合,可避免共线性问题,由前体物浓度和气象要素给出较好的北京大气O3浓度统计预报方程,可决系数R2分别为0.78(IAPs2007)、0.88(IRSAs2007)和0.64(IAPs2005),能够有效地预报O3浓度的变化情况.     

气象因素与早稻产量因子的相关性分析

为了探明气象因素对南方稻区早稻产量因子及产量的影响,应用杂交早稻组合金优402于2003—2009年种植在湖南省内7个生态点的产量因子和相应的气象数据,建立早稻不同生育时期的日平均气温、日最高气温、日最低气温、相对湿度和日照时数等气象因素与总苗数、成穗率、每穗总粒数、结实率、千粒重等产量因子的回归方程,研究影响湖南早稻产量因子的主要气象因素及其敏感时期。结果表明:移栽后24～27 d的低温阴雨导致早稻分蘖数不足;分蘖成穗率主要受移栽后33～41 d的气温和日照时数影响,随温度升高和日照时数延长而升高;每穗总粒数与始穗前9～1 d的日均温、始穗前9～4 d的日最高气温及始穗前10～5 d的日照时数呈正相关,而与此期的相对湿度呈负相关;结实率与始穗前14～9 d的日均温、日最低气温呈正相关,而与始穗前9～5 d的日最高气温和日照时数表现为负相关;千粒重与始穗前25～20 d的相对湿度、始穗后14～20 d的日照时数呈正相关,而与始穗前25～20 d的日均温、始穗后17～22d的日最低气温表现出负相关。     

基于遥感的黑河流域生态环境变化特征及成因分析

使用2001~2017年MODIS-EVI产品和2001,2009,2017年Landsat数据提取的湿度指数（WI）、沙漠化指数（DI）、改进归一化水体指数（MNDWI）,并结合气象数据及其它数据,揭示黑河流域生态环境变化特征.结果显示：近17a来,研究区低、中高和高植被覆盖区的面积分别以36,29,132km²/a的速率增加,无植被、中植被覆盖区面积以185,11km²/a的速率递减,且夏季和上游植被覆盖度最高;2001~2009年流域水域面积扩大至3854.5km²,2009~2017年减少至2628.9km²,上游地区水体较多,水量由山岭向山麓递减,由西向东递增;流域湿度指数由2001年0.55上升到2017年0.65,高值中心主要位于上游地区和中游民乐县、山丹县以及金塔县;流域沙漠化程度先逆转后扩展,沙漠化土地主要分布于中游高台县、临泽县、金塔县和下游额济纳旗;流域气温、降水、潜在蒸散量和地区生产总值、第一产业、建成区面积及耕地面积是影响黑河流域生态环境变化的主要驱动因素.     

上海地区大气相对湿度与PM10浓度和大气能见度的相关性分析

以大气RH(相对湿度)为基准对上海2005─2009年大气质量和气象资料的日均观测资料进行了分类统计,分析了RH与ρ(PM10)、大气能见度的相关关系. 结果表明:在将RH以5%的间隔进行分段后,各区段ρ(PM10)平均值与RH平均值呈显著线性负相关,R(相关系数)达0.97;随着RH增大,大气能见度随ρ(PM10)变化率的绝对值增大;RH在75%以上时,增加相同的ρ(PM10)所导致的大气能见度下降量是RH在40%~45%时的5倍以上;RH小于75%时,大气能见度可较好地反映ρ(PM10)的变化,而RH大于75%时,大气能见度的降低主要反映PM10含水量的快速增加而并不指示ρ(PM10)的增加.      

基于生态功能考虑的西北干旱地区生态需水研究

在当前生态需水研究的基础上,选取植被盖度作为衡量绿洲生态功能的主要指标,根据植被盖度和侵蚀率之间的关系,从生态系统的需水机理出发,提出了基于生态功能考虑的西北干旱地区生态需水量计算方法.以额济纳绿洲为例,计算了2000年额济纳绿洲生态需水,并与额济纳绿洲不同时期的生态需水进行了对比分析.     

A land use regression model incorporating data on industrial point source pollution

Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression (LUR) models for SO₂, NO₂ and PM₁₀ for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SO₂, NO₂ and PM₁₀ concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types (agricultural land, industrial land, commercial land, residential land, green space and water area) within different buffer radii (1 to 20 km). This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO₂ and NO₂. R² values of the multiple linear regression equations for SO₂, NO₂ and PM₁₀ were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables (such as traffic variables or meteorological condition variables), the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.     

白洋淀流域径流过程对极端气象干旱的响应分析

以白洋淀流域为研究对象,选取唐河、沙河、白沟引河3条支流上游4个水文站1959—2016年的日径流数据,采用改进退水常数后的数字滤波法中的Chapman-Maxwell法对4个子流域的日径流进行基流分割,利用水文气象要素异常值法划分干旱时期,分析水文干旱（径流干旱与基流干旱）对极端气象干旱过程的响应规律。结果表明:1）白洋淀年降水量呈减少趋势,线性倾向率为1.81 mm/a2。在1979年发生减少突变,突变后降水量减少8%;并检测到白洋淀流域发生极端气象干旱,持续时间从1996年8月至2011年5月;2）4个子流域的水文干旱较气象干旱具有明显的时间滞后,且水文干旱持续时间比气象干旱更长,烈度、强度更大,表明长期干旱期间降雨-径流关系的不稳定性;3）4个子流域水文恢复时间较气象恢复平均滞后55个月,且基流恢复滞后于径流恢复。研究结果可加深径流与基流对气候变化的响应的理解,为核算河道生态需水以及维持河道生态系统健康提供一定理论依据和实践参照。     

Estimates of the association between ozone and asthma hospitalizations that account for behavioral responses to air quality information

Behavioral responses to information about forecasted air quality may introduce systematic measurement error in pollution exposure, leading to biased estimates of the impact of pollution exposure on health. This paper estimates the statistical association between ambient ozone concentrations and asthma hospitalizations in Southern California while accounting for potential avoidance behavior in response to forecasted air quality. Data on asthma hospital admissions were merged with observed and forecasted air quality and meteorological data at the daily level for the years 1989–1997. A distributed lag Poisson generalized linear model allowing for overdispersion was estimated. Accounting for potential responses to information about pollution leads to significantly larger estimates of the relationship between ozone concentrations and asthma hospital admissions, particularly for susceptible populations. Individuals take substantial actions to reduce exposure to ozone; estimates of the concentration–response function for ozone that ignore these actions are biased towards the null and may significantly understate the costs to society from ozone concentrations.     

广州市主干道附近大气污染物浓度的特征及影响因素研究

为研究城市主干道边的空气污染状况,通过采用自动监测系统,在2007年1月至2月期间,对广州市新港西路两侧以及附近大学校园内的空气质量进行监测,获得了其空气污染物浓度的特征：（1）空气污染水平高,NO2与PM10日均值超标率较高;（2）污染物时空分布不均匀,NO浓度白天通常比夜间高,路边监测点NO小时浓度为校园对照点浓度的3倍左右。同时,分析了污染物浓度与气象条件及主干道交通流量的关系。结果表明：污染物浓度与气象因素之间有较高的多元线性相关性,但与单个因素的相关性不强;路边监测点的NO小时浓度和校园对照点的N0。小时浓度均与车流量有较高的相关系数,而PM10与车流量无显著相关性。综合考虑气象因素与交通流时,多元线性回归方程的复相关系数更高。     

基于多源辅助数据和神经网络模型的稻田土壤砷空间分布预测

合适的方法和多源的辅助数据对于准确预测土壤重金属的空间分布具有重要意义.该研究提出一种径向基函数神经网络结合普通克里格法的模型(RBFNN_OK),由主成分分析(PCA)提取的地形因子、遥感数据和邻近信息等多源辅助数据作为自变量,预测江西省都昌县稻田土壤砷空间分布.为验证RBFNN_OK的可行性:首先在全县范围内采集144个稻田表层(0～20 cm)土壤样品,运用ArcGIS地统计模块随机抽取115个(80%)采样点作为测试集,29个(20%)采样点作为验证集.其次多源辅助数据包括地形因子、遥感数据和邻近信息等14个定量因子作为预测变量,将预测变量进行主成分分析,得到前10个主成分的累积贡献率达到97.62%.再次一个特定的RBFNN_OK被用来预测土壤砷空间分布.最后将RBFNN_OK模型的预测结果与径向基神经网络模型(RBFNN)、回归克里格模型(RK)和多元逐步线性回归模型(MSLR)进行比较.结果表明,RBFNN_OK的测量值标准偏差与均方根误差的比值(RPD)较其它3种方法分别提高了14.92%、35.71%和44.67%.此外,RBFNN_OK还提供了更加真实且有关土壤砷空间分布的细节信息.RBFNN_OK取得最优效果可能归因于引入多源辅助数据,考虑多源辅助数据和土壤砷之间的多重共线性和非线性关系.该方法可为稻田土壤砷调查与环境保护提供更为精准的信息.     

土壤中矿物油含量测定方法的研究

重点介绍了以四氯化碳为萃取剂,利用超声波清洗仪萃取土壤中的油类物质,红外分光光度法测定土壤中的矿物油含量的方法。实验表明此方法具有良好的线性关系,相关系数可达0．9999。方法检出限为0．50mg／kg。平行样品间分析、试剂空白加标与基体加标回收率均能满足样品分析对精密度和准确度的要求。     

The affect of industrial activities on zinc in alluvial Egyptian soil determined using neutron activation analysis

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黑龙江省重点城市AQI指数特征及其与气象要素之关系

空气质量状况的优劣,直接关系到人体健康和经济社会可持续发展。利用2014年黑龙江省4个重点城市的空气质量数据,结合同期常规气象要素资料,分析了黑龙江省AQI指数基本特征及与气象要素的关系。分析结果表明：黑龙江省重点城市年平均AQI指数以哈尔滨最大（轻度污染级别）,其次牡丹江、大庆、齐齐哈尔（良级别）;单日空气质量指数最高值在大庆（500）,其次是哈尔滨（490）,牡丹江和齐齐哈尔单日最高值分别为264和251;AQI指数年分布特征是冬季最高,其次秋季,再次春季,夏季最低;首要污染物最多的是PM_2.5,其次PM₁₀、NO₂和臭氧8 h。AQI指数与平均气温,在年尺度上呈负相关,月和四季呈正相关为主;与降水日呈负相关;与相对湿度是冷月（1-2月）呈正相关,渐暖月（5-6月）呈负相关;与最大风速,采暖季呈明显负相关;与本站气压呈正相关,与日照时数冬季呈负相关关系。     

Modelling soil organic carbon dynamics in two long-term experiments of north-eastern Italy

Simulation models are widely used to assess the impacts of management and environmental variables on soil organic matter dynamics, to address questions on ecosystem sustainability and carbon cycling under global change. We tested the Century ecosystem model for two long-term experiments in north-eastern Italy: one (SF) comparing nutrient management treatments in small confined plots containing widely contrasting soil types (i.e., sandy, clay and peat) and the other (CR) involving a field study with crop rotation, nutrient, and management intensity variables. The organic matter changes in the SF experiment, showed a strong, linear relationship with C inputs from crop residues and added manures in the sand and clay soils, which was closely mimicked by the model. There was a net loss of soil C for all treatments in the peat soil, but the rate and overall magnitude of C losses were accurately simulated by the model, which suggested that treatment effects on soil C inputs was the major determinant of SOC dynamics in all three soils. In the CR experiment the model reasonably simulated the large initial decline (averaging about 30% of initial levels) in SOC observed in all treatments, as well as mean treatment effects over the course of the experiment. The model predicted a general pattern of higher SOC in the high management intensity, high fertility treatment combinations and lower SOC in the low management intensity, low fertility treatments; however, observed soil C did not show a clear pattern related to the treatments. Simulated soil C contents were linearly related to C input levels in the different treatments while there was no significant relationship between measured soil C and C inputs based on observed data.     

石家庄春季大气气溶胶的散射特征

利用2010年5月积分浊度仪、PCASP-X2和能见度仪的观测资料,分析了石家庄大气气溶胶的散射特征及其与气溶胶粒子浓度、能见度、气象条件的关系.结果表明,观测期间,450,550,700nm 3个波段的气溶胶散射系数平均值±标准差分别为(257±293),(199±237)和(143±173)Mm-1,散射系数的变化很大,但气溶胶微物理特征相对比较稳定.散射系数日变化呈3峰分布,峰值出现在8:00、13:00和0:00.以550nm波长为例,气溶胶散射系数的变化范围为144~308Mm-1,夜间散射系数大于白天,非晴天散射系数平均值(524.9Mm-1)是晴天散射系数(112.3Mm-1)的4.7倍.气溶胶3个波段后向散射比均大于0.15,说明石家庄细粒子污染比较严重.散射系数和体积浓度成正比,但由于局地气象条件和污染源的影响,有气溶胶体积浓度变大,散射系数变化不大的情况出现.气溶胶散射系数和能见度呈负相关;根据Koschmieder公式计算得到的能见度,能较好反映实际观测情况.当大气相对湿度较高时,气溶胶散射系数随湿度增大呈现两种不同的变化趋势,即一部分气溶胶的散射系数有明显的增大,而另一部分则随着相对湿度的增加并未增大,反而比干气溶胶散射系数要小.局地风场也会影响气溶胶散射特性.     

沈阳市PM2.5浓度ARIMA-SVM组合预测研究

首先利用回归树分类方法,对采暖期与非采暖期各日进行气象类型划分,识别出易造成重污染天气的气象类型.其次分别在各气象类型内,以污染源排放量为自变量,利用差分自回归滑动平均与支持向量机（ARIMA+SVM）组合方法建立起PM_2.5浓度日均值预测模型,并选取2013年01月~2017年06月间,沈阳市区内9个环境监测点PM_2.5浓度日均值进行实证分析.结果表明,使用气象分类下的ARIMA+SVM组合模型对PM_2.5浓度日均值进行预测,相比于不划分气象类型时的普通机器学习模型,其模型预测值与实测值趋势的吻合度更高,且对峰-谷值的识别能力更强.在采暖期与非采暖期,组合模型均具有平均绝对误差更低、预测正确率更高的优点.     

Forecasting particulate pollutant concentrations in a city from meteorological variables and regional weather patterns

A synoptic meteorological classification and its correlation with particulate matter concentrations collected at five sampler points in the city of Valladolid (Spain) have been performed by means of a Q-mode clustering technique.The application of the algorithm to 11 meteorological variables related to the surface level and to the 500-hPa contour has permitted us to identify five synoptic meteorological types which have been split into nine synoptic meteorological classes. Also, the algorithm has been applied to the particulate matter concentrations recorded at each sampler point, and seven pollution levels have been obtained in each of them. The comparison between the days corresponding to the five synoptic meteorological types and the days included in each of the seven pollution clusters of every sampler point has revealed a satisfactory relationship between the particulate matter concentrations and the identified meteorological types at the 500-hPa contour.