Nitrogen deposition effects on Mediterranean-type ecosystems: an ecological assessment

We review the ecological consequences of N deposition on the five Mediterranean regions of the world. Seasonality of precipitation and fires regulate the N cycle in these water-limited ecosystems, where dry N deposition dominates. Nitrogen accumulation in soils and on plant surfaces results in peaks of availability with the first winter rains. Decoupling between N flushes and plant demand promotes losses via leaching and gas emissions. Differences in P availability may control the response to N inputs and susceptibility to exotic plant invasion. Invasive grasses accumulate as fuel during the dry season, altering fire regimes. California and the Mediterranean Basin are the most threatened by N deposition; however, there is limited evidence for N deposition impacts outside of California. Consequently, more research is needed to determine critical loads for each region and vegetation type based on the most sensitive elements, such as changes in lichen species composition and N cycling.     

江苏省太湖流域水功能区纳污能力及限制排污总量研究

水功能区纳污能力及限制排污总量研究是制定区域水污染控制规划的基础。依据《江苏省地表水(环境)功能区划》,结合江苏省太湖流域现状水质和污染概况,针对河网区和湖库区分别采用一维、二维非稳态模型,计算江苏省太湖流域水功能区纳污能力,在此基础上,引入最大污染物入河量,核定50%、75%和90%水文保证率下的最大污染物入河量分别为2015年、2020年和2030年限排总量。结果表明:(1)CODMn和氨氮纳污能力分别为284 803 t/a和22 448 t/a;(2)2015年CODMn和氨氮限排总量分别为221 867 t/a和20 520 t/a,2020年和2030年限排总量递减,均小于纳污能力;(3)CODMn和氨氮入河量削减率分别为21.8%和46.3%,与水质超标率相差均在25%以内,基本相符。江苏省太湖流域纳污能力、限排总量、污染物入河量削减率和水质超标率之间关系合理,计算结果合理。研究成果为太湖流域水环境控制规划提供决策依据。     

流域经济增长空间分异研究——基于2001～2009年长江流域数据的面板计量分析

流域经济是以水系为轴线的区域经济,其发展状况对国民经济有重要影响,其研究为区域开发提供新视角。在理论方法上,根据内生经济增长理论,采用柯布 道格拉斯生产函数,构建一个包括技术进步、物质资本和人力资本作为内生要素的流域经济增长框架。在实践论证上,以长江为样本域,运用面板计量分析方法,测度生产要素对流域上中下游经济增长的影响。结果显示：不同生产要素对流域经济不同域段作用强度不同,且呈现出明显的梯度效应,即沿江而下,技术进步和人力资本对经济增长的贡献度逐渐加大,物质资本则恰好相反。在此基础上,提出缩小流域经济的不平衡程度的政策建议,主要包括促使流域上游地区人力资本开发、实施流域大开发战略和推进流域城市化等     

基于GIS和组合赋权法的农村生态功能适宜性评价及管制分区

在村级土地利用规划过程中进行生态功能适宜性评价,以了解农村生态质量状况、明确农村生态功能适宜程度及空间分布,为村级土地利用规划中土地利用方向的确定和空间布局的划分提供科学的生态适宜依据,从而更好地协调农村发展建设和生态环境保护的关系有着至关重要的作用。以岩南村为例,开展了农村生态功能适宜性评价及应用研究。以高分辨率航空影像为数据源,从地形条件、土壤资源、生物资源、水资源、人类干扰5个方面建立了评价指标体系;利用组合赋权法确定各评价因子的权重值,构建了生态功能适宜性评价模型;以栅格为评价单元,在GIS支持下,对岩南村进行生态功能适宜性评价。并根据评价结果划分了生态功能适宜等级,制定了分区管制措施,提出了土地利用建议,旨在为岩南村土地利用规划提供指导     

低碳消费偏好与低碳产品需求分析

低碳消费方式是低碳经济的重要环节,本文对低碳消费偏好和低碳产品需求及其影响因素作了理论分析和实证研究.首先对低碳产品的消费偏好进行了分析,低碳产品消费偏好的两个最重要特征是二元价值结构的产品和超越基本价值的消费偏好,在此基础上构建了低碳产品效用函数.然后根据低碳产品效用函数给出了低碳产品的一般需求模式,结合低碳产品置信度变量的引进,构建了一个具体的低碳产品需求函数,并对低碳产品需求函数进行分析,揭示了低碳产品需求的一些基本性质.为了验证低碳消费理论分析的结论,做了低碳产品消费的问卷调查.对问卷调查进行统计分析,结果表明:收入越高,对低碳产品支付的价格就越高;低碳产品的环境价值置信度越高,意愿支付价格就越商;低碳产品碳排放量降低越多,低碳产品需求价格就越高.最后,结合以上分析,从低碳宣传和公益广告、设立低碳产品标准、鼓励低碳产品技术研发角度提出了促进低碳消费发展的政策建议.     

中国碳排放强度与煤炭消耗的冲击效应分析

受能源消费结构的影响,煤炭作为我国经济发展的资源支柱,一方面推动着经济快速增长,另一方面也对中国节能减排、降低碳排放强度提出了挑战,因而准确认识碳排放强度与煤炭消耗之间的交互冲击作用机理,为挖掘碳减排路径提供了科学依据.本文选取1990 - 2008年间中国碳排放强度与煤炭消耗指标,采用EG协整检验证明碳排放强度与煤炭消耗之间存在长期稳定关系,并以此建立VAR模型和脉冲响应函数,考察碳排放强度与煤炭消耗之间的长期动态影响特征.冲击响应分析结果表明:(1)煤炭消耗比重的变化对碳排放强度的冲击影晌具有一定滞后性和波动性,但冲击作用长期持久;(2)碳排放强度对煤炭消耗比重的冲击影响在短期内较剧烈,但长期冲击影响不明显;(3)煤炭消耗比重的降低在长期内会促使碳排放强度的降低,因而可以通过降低煤炭消耗比重来达到降低碳排放强度的目的.最后,从结构性降低、产业传导性降低以及技术性降低等角度,提出减少煤炭消耗、降低碳排放强度的相关对策措施.     

Chemical fluxes in time through forest ecosystems in the UK - Soil response to pollution recovery

Long term trend analysis of bulk precipitation, throughfall and soil solution elemental fluxes from 12 years monitoring at 10 ICP Level II forest sites in the UK reveal coherent national chemical trends indicating recovery from sulphur deposition and acidification. Soil solution pH increased and sulphate and aluminium decreased at most sites. Trends in nitrogen were variable and dependant on its form. Dissolved organic nitrogen increased in bulk precipitation, throughfall and soil solution at most sites. Nitrate in soil solution declined at sites receiving high nitrogen deposition. Increase in soil dissolved organic carbon was detected - a response to pollution recovery, changes in soil temperature and/or increased microbial activity. An increase of sodium and chloride was evident - a possible result of more frequent storm events at exposed sites. The intensive and integrated nature of monitoring enables the relationships between climate/pollutant exposure and chemical/biological response in forestry to be explored.     

Estimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested

Oxygen (O₂), nitrate (NO₃), dissolved inorganic carbon (DIC) or pCO₂, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying time-scales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O₂, NO₃, DIC, pCO₂, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O₂, NO₃, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings.Smoothing of the data to remove data noise before assimilation improves the estimation of the biogeochemical rates. The best estimated rates are obtained when assimilating O₂, NO₃ and TA although the assimilation of DIC instead of TA also gives satisfactory results. In case pH or pCO₂ is assimilated rather than DIC or TA, the linearization of the (now nonlinear) observation equation introduces perturbations and the Kalman filter behaves suboptimal. We conclude that, given the resolution of data required, the tool has potential to estimate biogeochemical rates of the carbonate system under controlled settings.     

COMPARISON OF REGRESSION AND TIME-SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS1

ABSTRACT: Regression and time-series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time-series model was able to eliminate. The time-series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.