内蒙古气温变暖停滞对其影响因子变化的响应

采用中心聚类、M-K检验等方法,以内蒙古地区为例,利用全球Pacific Decadal Oscillation（PDO）、Multivariate ENSO Index（MEI）等大空间尺度数据以及内蒙古及其周边70个气象站1951~2016年平均最低气温、平均气温、平均最高气温、风速、大气压等站点数据,定性、定量揭示变暖停滞的变化特征及其对影响因子变化的响应.结果表明：研究区各分区3类气温在1981~1993年间发生升温突变,此后1998~2008年间陆续发生变暖停滞.不同类型气温在不同分区与各影响因子的相关性优劣有所不同,如平均最低气温与AMO、PDO、MEI、太阳总辐射、风速、大气压的相关性最好,平均气温次之,平均最高气温最差;西部区气温与AMO、PDO、MEI、太阳总辐射相关性较好,中部区气温则与AMO、风速相关性较好等.整体上,1990s~2000s,随各分区AMO上升驱缓、PDO处于正位相阶段但呈下降趋势或处于负位相时、MEI值与太阳总辐射下降、风速、大气压、相对湿度的持续下降/上升及之后的趋势转变,各分区气温发生变暖停滞,如当AMO开始整体进入上升趋缓阶段,风速持续减小8~13a,倾向率达到-0.26~-0.11m/（s·10a）时,平均气温发生变暖停滞.平均最低气温对3类影响因子变化的响应最敏感,平均气温次之.气温变暖停滞是多种影响因子共同作用的结果.本研究丰富了该方面研究成果,对气候变化研究及防灾减灾等有一定借鉴意义.     

轮作方式对冬水田温室气体排放的影响

以位于西南大学农业部重庆紫色土生态环境重点野外科学观测试验站内的冬水田(RF)、水稻-油菜轮作(RR)和水稻-儿菜轮作(RV)农田为研究对象,采用静态箱-气相色谱法对农田的温室气体的排放通量进行了为期一年的原位观测,其中采用静态暗箱技术观测CH4和N2O,静态明箱技术观测CO2.结果表明,不同轮作方式下CH4的年排放总量[以CH4计,kg·hm-2]RF(422.87±27.1) RR(132.05±23.11) RV(50.91±3.83),其中RV与RR处理较RF处理CH4排放量有明显下降(P0.05);N2O的年排放总量[以N2O计,kg·hm-2]依次为RV(21.38±6.51) RR(20.02±5.23) RF(0.48±0.02),RV和RR处理N2O的排放总量均显著高于RF(P0.05);CO2的年净排放总量[以CO2计,t·hm-2]为RR(-55.43±5.04) RV(-29.1±3.00) RF(-14.08±1.81),RV和RR处理CO2的吸收量显著高于RF处理(P0.05).在100a时间尺度上,全年排放的CH4、N2O和CO2所引起综合GWP(以CO2计,t·hm-2)为RR(-46.43) RV(-22.01) RF(-2.11),表明冬水田转变为水旱轮作系统后能显著提升农田生态系统的增汇效果,相比于RV处理,RR处理增汇效果更好,即在西南地区水稻-油菜轮作农田在生态系统增汇上是一种最有效的轮作方式.     

江苏省人为源VOCs排放清单及其对臭氧生成贡献

基于江苏省工业、能源、环境等活动水平数据,结合排放因子法和源成分谱研究成果,建立了江苏省分市、分行业、分物种人为源VOCs排放清单,利用最大增量反应活性(MIR)估算了其对臭氧的生成贡献.结果显示,江苏省2015年VOCs人为源排放量为192.78万t,化石燃料燃烧、工业过程源、有机溶剂使用源、生物质燃烧源、移动源、有机溶剂储运源排放质量分数分别为7.38%、27.93%、39.56%、3.55%、16.18%、5.39%.苏州、南京、徐州3市VOCs排放量居全省前三位,均超过20万t.56种臭氧前驱物所产生的臭氧生成潜势(OFP)总量为542.95万t,行业分布与VOCs排放总量的行业分布相似,机械设备制造、交通工具制造、建筑装饰等涂装行业对OFP的贡献比例是VOCs排放总量贡献比例的1.3~1.6倍,控制喷涂行业等量的VOCs会产生更大的OFP削减.对OFP贡献大的前10位物种分别是间/对-二甲苯、乙烯、丙烯、1,3-丁二烯、甲苯、邻-二甲苯、1-丁烯、乙苯、1,2,4-三甲基苯、对-乙基甲苯,对总OFP的贡献为75.63%.     

沈阳工业区夏季VOCs组成特征及其对二次污染形成的贡献

利用2019年和2020年夏季沈阳市工业区大气挥发性有机物(VOCs)的观测数据,研究沈阳市夏季工业区大气VOCs的组成特征并初步判断其来源,并利用最大增量反应活性(MIR)和气溶胶生成系数(FAC)法分别估算该地大气VOCs的臭氧生成潜势(OFP)及二次有机气溶胶生成潜势(AFP).结果表明,观测期间沈阳市工业区ρ(总VOCs)平均值为41.66μg·m^-3,烷烃、烯烃、芳香烃和乙炔分别占总VOCs浓度的48.50%、 14.08%、 15.37%和22.05%.浓度排名前10的物种累计占总VOCs浓度的69.25%,其中大部分为C2～C5的烷烃,还包括乙炔、乙烯和部分芳香烃.总VOCs整体上呈现出早晚浓度高、中午浓度低的日变化特征,峰值分别出现在06:00和22:00,11:00～16:00处于较低水平.由甲苯/苯(T/B)和异戊烷/正戊烷的比值判断工业区主要受机动车尾气排放、溶剂使用、燃烧源和LPG/NG的影响.工业区大气VOCs的总AFP为41.43×10^-2μg·m^-3,其中芳香烃的贡献最大;总OFP贡献值为1...     

基于PMF-PCA/APCS与PERI的菏泽油用牡丹种植区表层土壤重金属潜在来源识别及生态风险评估

研究特色农产品产区土壤重金属来源及其潜在风险,对科学管理、安全利用土壤和作物资源具有重要意义.以菏泽油用牡丹种植区为研究对象,采集并测定了254件表层土壤样品As、Cd、Cr、Cu、Hg、Ni、Pb和Zn等8种重金属的含量.采用多元统计法分析了重金属的含量特征及相关性,利用地累积指数（I_geo）、正定矩阵因子分解法（PMF）和主成分分析/绝对主成分分数法（PCA/APCS）相结合的手段解析了表层土壤中重金属的来源,借助潜在生态风险指数（PERI）对该8种重金属的生态风险进行了评估.结果表明,土壤中除Cd元素的平均值高于菏泽市背景值1.44倍之外,其余7种重金属的平均含量均与菏泽市土壤元素背景值基本一致;经相关分析和聚类分析,土壤中Pb、Hg和Cd元素受后期人为活动的干扰影响较大;研究区8种重金属的来源为自然源、农业化肥源、工业燃煤源和生活交通源,贡献率分别为81.31%、15.45%、2.74%和0.50%;研究区84.25%的点位处于轻微生态风险,而中度风险和强风险点位占比分别为14.96%和0.79%,其中Cd和Hg是研究区生态风险主导元素.     

湘东北典型河源区土壤重金属分布特征、来源解析及潜在生态风险评价

水源地土壤环境质量状况关乎其流域内居民生命健康安全,是生态环境保护研究中的热点科学问题.选择湘东北典型河源区,采集表层土壤样品共87件,通过GIS技术和潜在生态风险指数法研究了土壤重金属（Cd、Pb、Cr、Hg和As）的空间分布特征和潜在生态风险,并采用多元统计分析和正定矩阵因子分解（PMF）模型解释了其可能来源和贡献率.结果表明：①湘东北典型河源区土壤呈酸性,土壤重金属ω（Cd）、ω（Pb）、ω（Cr）、ω（Hg）和ω（As）平均值分别为0.20、41.07、130.51、0.29和11.63mg ·kg^-1,对标背景值,除As外均有富集;②土壤重金属综合潜在生态风险为中等风险等级,其中Cr、Pb和As为轻微风险等级,Cd和Hg均为强风险等级;③土壤Cd和Pb具有同源性,主要来源于农业活动,Cr和As受生活垃圾排放和自然母质的双重影响,Hg主要来源于化石燃烧及交通运输;④生活垃圾排放源、自然母质源、化石燃烧及交通运输源和农业活动源对湘东北典型河源区土壤重金属的贡献率分别为21.36%、35.92%、19.30%和23.42%,人为源贡献率大于自然源.研究结果对湘东北典型河源区的污染防治、生态修复和美丽乡村建设具有参考价值.     

反硝化脱氮对太湖蓝藻水华态势的影响

反硝化作用是水生生态系统的主要脱氮过程,与蓝藻生长之间存在对氮素的竞争作用,然而气候变化背景下反硝化脱氮对蓝藻水华发生动态的影响仍不清楚.基于2017~2021年北太湖为期5 a的水质监测历史数据,结合不同温度下蓝藻生长和沉积物泥浆培养实验,探究了湖体反硝化脱氮与蓝藻水华之间的相互影响.监测数据表明,太湖水体藻类生物量（以Chla表示）高值主要出现在夏秋季节,而总氮浓度季节变化规律与藻类生物量完全相反,冬春季较高,夏秋季显著降低,溶解态无机氮主要以硝态氮为主,并且硝态氮浓度在夏秋季节几乎接近于零.总磷浓度与Chla浓度变化一致.蓝藻培养实验结果表明,20℃以下蓝藻不能大量生长繁殖.泥浆培养实验结果发现,太湖反硝化作用的最高温度阈值为25℃,在10~25℃之间反硝化潜力与温度呈现显著的线性关系（R²=0.99）.反硝化作用发生的最高硝态氮浓度阈值为4 mg ·L^-1,远高于太湖水体的硝态氮浓度,反硝化潜力最高达到（62.98±21.36）μmol ·（kg ·h）^-1.太湖水体反硝化速率受到硝态氮浓度的限制,而气候变暖导致湖泊温度提前升高,会使蓝藻提前生长,蓝藻生长对硝态氮的同化吸收会和反硝化作用产生竞争,使得大量氮还未被反硝化作用脱除就被藻类吸收利用,从而加剧蓝藻水华暴发的态势.研究结果对于解释近年来气候变化背景下太湖蓝藻水华反弹的机制具有重要科学意义.     

Global Warming and Global Dioxide Emission: An Empirical Study

In this paper, the dynamic relationship between global surface temperature (global warming) and global carbon dioxide emission (CO₂) is modelled and analyzed by causality and spectral analysis in the time domain and frequency domain, respectively. Historical data of global CO₂emission and global surface temperature anomalies over 129 years from 1860–1988 are used in this study. The causal relationship between the two phenomena is first examined using the Sim and Granger causality test in the time domain after the data series are filtered by ARIMA models. The Granger causal relationship is further scrutinized and confirmed by cross-spectral and multichannel spectral analysis in the frequency domain. The evidence found from both analyses proves that there is a positive causal relationship between the two variables. The time domain analysis suggests that Granger causality exists between global surface temperature and global CO₂emission. Further, CO₂emission causes the change in temperature. The conclusions are further confirmed by the frequency domain analysis, which indicates that the increase in CO₂emission causes climate warming because a high coherence exists between the two variables. Furthermore, it is proved that climate changes happen after an increase in CO₂emission, which confirms that the increase in CO₂emission does cause global warming.     

The interrelationships between resource-holding potential,resource-value and reproductive success in territorial males: How much variation can we explain?

A long-standing hypothesis in behavioural ecology posits that males with greater resource-holding potential (RHP) control resource sites deemed more valuable by sexually-receptive females and, thereby, males controlling such sites accrue greater reproductive success (RS). This hypothesis has historically been investigated using three separate but non-mutually exclusive relationships (male RHP vs. resource value, resource value vs. male RS and male RHP vs. RS). The relationships between these three variables are predicted to be strongly positive, however, due to measurement error and biological noise, perfect correlations (r = 1.0) are rare in biology even for well-established relationships. Moreover, the inaccurate identification of either the male trait(s) important to RHP or the resource characteristic sought by females will weaken the observed strength of the relationships. Here, I use meta-analysis to quantitatively describe the general pattern of these relationships in animals. I predict that the relationships between male RHP, resource-value and RS should be significantly positive (male RHP and resource-value should explain a large amount of the variation in male RS). My meta-analysis supports this hypothesis; however, in the best case scenario only ca. 20% of the variation in the response variable was explained. I conclude by identifying areas in which we need to improve our investigations of resource-defence animals and recommending approaches to meet these needs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Proposal of Indicators to Assess Urban Sustainability in Brazil

The research related here focuses on municipal situations where problems of sustainability may be defined and tackled on the basis of bottom-up management procedures with the participation of organized society. The aim is to build management models that may be implemented with reasonable administrative effort and cost. Implementation pursues the target of approaching a sustainable situation in the municipality. Environmental parameters for an ideal municipality with undefined geographical location are presented. For each parameter, a set of indicators is developed that can measure the prospect of sustainability. The indicators are defined in terms of numbers or literal concepts according to the possibility of measurement. Examples of management models are presented, which are able to approach the situation defined as sustainable by the indicators. The basic management tool is the learning curve of targeted communities, which is experimentally developed and applied. The indicators are grouped according to their range of applicability.