Low cost measurements of nitrogen and sulphur dry deposition velocities at a semi-alpine site: gradient measurements and a comparison with deposition model estimates

The conditional time averaged gradient method was used to measure air-surface exchange of nitrogen and sulphur compounds at a semi-alpine site in Southern Norway. Dry deposition velocities were then obtained from the bi-weekly concentration gradient measurements. Annual deposition velocities were found to be 1.4, 11.8 and 4.0 mm s(-1) for NH3, HNO3 and SO2, respectively, if all data were included, and to be 10.8, 11.8 and 13.0 mm s(-1), respectively, if only positive values were included. Measured deposition velocities were compared to two sets of values estimated from a big-leaf dry deposition module applying to two different land types (short grass and forbs, and tundra), driven by measured micrometeorological parameters. The deposition module gives reasonable values for this site throughout the year, but does not reproduce the large variability as shown in the measured data. No apparent seasonal variations were found from either measurements or module estimates due to the very low productivity of the studied area.     

环境监测技术培训需求分析——应用OTP模型

简述了环境监测技术培训需求分析的重要性及OTP模型的概念.针对环境监测技术培训的现状和特点,设计了符合环境监测技术培训特点的OTP模型,提出了系统分析环境监测技术培训需求的方法,以及根据实际情况科学设置输入项的不同权重,充分考虑影响模型输出的各种因素,加强研究模型输入项的量化表征,动态调整模型的输入项的建议.     

中国工业碳排放达峰的情景预测与减排潜力评估

实现2030年碳排放达峰不仅是中国为应对全球气候变化向国际社会做出的郑重承诺,也是中国未来经济结构转型与可持续发展的必然选择。基于中国实现2030年碳排放达到峰值的宏观目标为背景,本文以中国碳排放的主要行业工业为研究对象,首先运用拓展的STIRPAT模型对工业及其9个细分行业的碳排放达峰进行了情景预测,然后基于公平和效率的双重视角对工业细分行业的减排潜力进行评估。研究表明:(1)仅有低碳情景和抑制排放情景2可以实现中国碳排放2030年达峰,低碳情景是实现中国工业碳排放达峰的最佳发展模式,达峰时间最早(2030年),峰值最低(140.43亿t)。激进排放情景则是最差的发展模式,达峰时间最晚(2036年),峰值也最高(150.09亿t)。(2)工业内部各细分行业碳排放的最优达峰情景差别较大。建材和纺织制造业能够实现提前达峰,可以在这类行业率先实施达峰管理措施,使其带动其他行业陆续达峰。(3)最具减排潜力的行业是石油制造业,其次是电力行业,这些减排潜力较大的行业应该成为国家节能减排的重点对象。(4)基于工业各细分行业在减排公平性和效率性上的差异将工业9个细分行业分为四类。其中,石油、钢铁制造业和电力行业属于"高效高公平行业";化工、建材制造业属于"低效高公平行业";采掘业属于"高效不公平行业";纺织、轻工和机电制造业属于"低效不公平行业"。中国应针对不同类型的行业制定出相应的减排战略,将减排重点放在各行业最具潜力的方面。最后,文章对实现中国工业碳排放达峰管理提出了几点政策建议。     

Comparison of the daily global solar radiation from different data sources in Northwest China climate

The solar radiation data are of high importance to the solar energy systems. Conventional methods to obtain the solar radiation data are from weather stations, solar radiation models, commercial software databases, and field measurements. In the present study, a new daily global solar radiation model is proposed, by combining the quadratic function of sunshine fraction and sine function of the day of the year. The solar radiation model calculated data are then compared with China Meteorological Data Sharing System (CMDSS) data, TRNSYS data, and field-measured data in Northwest China climate. It is found that the newly proposed solar radiation model has better performance than the other nine solar radiation models in the literature. The solar radiation model calculated data fit well with the CMDSS annually average data. The TRNSYS data are a bit larger than the CMDSS annually average data in summer half year and a little smaller than those in winter half year. The solar radiation model and the CMDSS annually average data have the best correlation, whereas the TRNSYS data and the field-measured data have the worst correlation. The solar radiation model calculated data have the best correlation with the other three data sources.     

秦皇岛市“创模”对策研究及效益分析

介绍了秦皇岛市创建国家环境保护模范城市的意义,重点阐述了完成创模任务的主要对策,包括:构建以旅游业为中心、特色产业互融互促的现代产业体系;加快城乡一体化建设;提升城镇发展质量和水平;加强重大基础设施建设;积极推广清洁能源,深入开展工程节能;积极推进循环经济发展等。秦皇岛市创建国家环境保护模范城市,将会在环境、经济和社会三方面产生明显的综合效益。     

喀斯特峡谷区工程性缺水原因及解决途径——以贵州省花江峡谷示范区为例

喀斯特峡谷区河深坡陡,地下水深埋,水资源利用难度大,加之经济和水利工程薄弱,是贵州省工程性缺水的典型区域。通过对花江峡谷示范区工程性缺水的原因剖析,提出一系列解决工程性缺水问题的措施,如雨水收集、表层喀斯特水和基岩裂隙水的开发利用、节水、加强对水利工程设施的管理和维护、加大水利投入以及提高植被覆盖率等,这对解决喀斯特峡谷及类似区域的工程性缺水问题有一定的指导和参考意义。     

Modelling the fate of hydrophobic organic contaminants in a boreal forest catchment: A cross disciplinary approach to assessing diffuse pollution to surface waters

The fate of hydrophobic organic compounds (HOCs) in soils and waters in a northern boreal catchment was explored through the development of a chemical fate model in a well-characterised catchment system dominated by two land types: forest and mire. Input was based solely on atmospheric deposition, dominated by accumulation in the winter snowpack. Release from soils was governed by the HOC concentration in soil, the soil organic carbon fraction and soil-water DOC content. The modelled export of selected HOCs in surface waters ranged between 11 and 250 ng day⁻¹ during the snow covered period, compared to 200 and 9600 ng/d during snow-melt; highlighting the importance of the snow pack as a source of these chemicals. The predicted levels of HOCs in surface water were in reasonable agreement to a limited set of measured values, although the model tended to over predict concentrations of HOCs for the forested sub-catchment, by over an order of magnitude in the case of hexachlorobenzene and PCB 180. This possibly reflects both the heterogeneity of the forest soils and the complicated and changing hydrology experienced between the different seasons.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Quantification of nitrate leaching from German forest ecosystems by use of a process oriented biogeochemical model

Simulations with the process oriented Forest-DNDC model showed reasonable to good agreement with observations of soil water contents of different soil layers, annual amounts of seepage water and approximated rates of nitrate leaching at 79 sites across Germany. Following site evaluation, Forest-DNDC was coupled to a GIS to assess nitrate leaching from German forest ecosystems for the year 2000. At national scale leaching rates varied in a range of 0–>80 kg NO₃–N ha⁻¹ yr⁻¹ (mean 5.5 kg NO₃–N ha⁻¹ yr⁻¹). A comparison of regional simulations with the results of a nitrate inventory study for Bavaria showed that measured and simulated percentages for different nitrate leaching classes (0–5 kg N ha⁻¹ yr⁻¹:66% vs. 74%, 5–15 kg N ha⁻¹ yr⁻¹:20% vs. 20%, >15 kg N ha⁻¹ yr⁻¹:14% vs. 6%) were in good agreement. Mean nitrate concentrations in seepage water ranged between 0 and 23 mg NO₃–N l⁻¹.     

Evaluating and reducing a model of radiocaesium soil-plant uptake

An existing model of radiocaesium transfer to grasses was extended to include wheat and barley and parameterised using data from a wide range of soils and contact times. The model structure was revised and evaluated using a subset of the available data which was not used for model parameterisation. The resulting model was then used as a basis for systematic model reduction to test the utility of the model components. This analysis suggested that the use of 4 model variables (relating to radiocaesium adsorption on organic matter and the pH sensitivity of soil solution potassium concentration) and 1 model input (pH) are not required. The results of this analysis were used to develop a reduced model which was further evaluated in terms of comparisons to observations. The reduced model had an improved empirical performance and fewer adjustable parameters and soil characteristic inputs.