Investigation of carbonyl compound sources at a rural site in the Yangtze River Delta region of China

Carbonyl compounds are important intermediates in atmospheric photochemistry, but their primary sources are still not understood well. In this work, carbonyls, hydrocarbons, and alkyl nitrates were continuously measured during November 2011 at a rural site in the Yangtze River Delta region of China. Mixing ratios of carbonyls and hydrocarbons showed large fluctuations during the entire measurement. The average level for total measured volatile organic compounds during the pollution episode from 25th to 27th November, 2011 was 91.6 ppb, about 7 times the value for the clean period of 7th-8th, November, 2011. To preliminarily identify toluene sources at this site, the emission ratio of toluene to benzene (T/B) during the pollution episode was determined based on photochemical ages derived from the relationship of alkyl nitrates to their parent alkanes. The calculated T/B was 5.8 ppb/ppb, significantly higher than the values of 0.2-1.7 ppb/ppb for vehicular exhaust and other combustion sources, indicating the dominant influence of industrial emissions on ambient toluene. The contributions of industrial sources to ambient carbonyls were then calculated using a multiple linear regression fit model that used toluene and alkyl nitrates as respective tracers for industrial emission and secondary production. During the pollution episode, 18.5%, 69.0%, and 52.9% of measured formaldehyde, acetaldehyde, and acetone were considered to be attributable to industrial emissions. The emission ratios relative to toluene for formaldehyde, acetaldehyde, and acetone were determined to be 0.10, 0.20 and 0.40 ppb/ppb, respectively. More research on industrial carbonyl emission characteristics is needed to understand carbonyl sources better.     

Insights into metals in individual fine particles from municipal solid waste using synchrotron radiation-based micro-analytical techniques

Excessive inter-contamination with heavy metals hampers the application of biological treatment products derived from mixed or mechanically-sorted municipal solid waste (MSW). In this study, we investigated fine particles of < 2 mm, which are small fractions in MSW but constitute a significant component of the total heavy metal content, using bulk detection techniques. A total of 17 individual fine particles were evaluated using synchrotron radiation-based micro-X-ray fluorescence and micro-X-ray diffraction. We also discussed the association, speciation and source apportionment of heavy metals. Metals were found to exist in a diffuse distribution with heterogeneous intensities and intense hot-spots of < 10 μm within the fine particles. Zn-Cu, Pb-Fe and Fe-Mn-Cr had significant correlations in terms of spatial distribution. The overlapped enrichment, spatial association, and the mineral phases of metals revealed the potential sources of fine particles from size-reduced waste fractions (such as scraps of organic wastes or ceramics) or from the importation of other particles. The diverse sources of heavy metal pollutants within the fine particles suggested that separate collection and treatment of the biodegradable waste fraction (such as food waste) is a preferable means of facilitating the beneficial utilization of the stabilized products.     

Insights into metals in individual fine particles from municipal solid waste using synchrotron radiation-based micro-analytical techniques

Excessive inter-contamination with heavy metals hampers the application of biological treatment products derived from mixed or mechanically-sorted municipal solid waste(MSW). In this study, we investigated fine particles of 2 mm, which are small fractions in MSW but constitute a significant component of the total heavy metal content, using bulk detection techniques. A total of 17 individual fine particles were evaluated using synchrotron radiation-based micro-X-ray fluorescence and micro-X-ray diffraction. We also discussed the association, speciation and source apportionment of heavy metals. Metals were found to exist in a diffuse distribution with heterogeneous intensities and intense hot-spots of 10 μm within the fine particles. Zn–Cu, Pb–Fe and Fe–Mn–Cr had significant correlations in terms of spatial distribution. The overlapped enrichment, spatial association, and the mineral phases of metals revealed the potential sources of fine particles from size-reduced waste fractions(such as scraps of organic wastes or ceramics) or from the importation of other particles. The diverse sources of heavy metal pollutants within the fine particles suggested that separate collection and treatment of the biodegradable waste fraction(such as food waste) is a preferable means of facilitating the beneficial utilization of the stabilized products.     

以植被生物完整性评价梁子湖湖滨湿地生态系统健康

湖滨湿地植被是湖滨带生态系统的主要特征,以湖滨湿地植被为对象可评价湖滨带生态系统健康状况。通过对梁子湖湖滨湿地植被的详细调查,共鉴定出植物182种,隶属于52科128属,其中湿生植物147种,水生植物35种。水生植物中有20种挺水植物,6种浮叶植物和9种沉水植物。采用植被生物完整性(VIBI)方法评价梁子湖湖滨湿地生态系统健康,对21个备选指标进行筛选分析,建立了以挺水植物物种数、多年生植物物种数、外来物种百分比、香农多样性指数、植物区系质量指数FQAI、耐受性物种百分比、敏感性物种百分比为核心指标的评价体系,三分法对指标进行赋值,将梁子湖湖滨湿地划分为健康、良好、一般和较差4个等级。评价结果表明,梁子湖湖滨湿地22个调查位点中,处于健康状态的有3个位点,良好6个,共占总位点数的41%,一般和较差分别为7个和6个,共占59%。总体上看,东梁子湖和牛山湖湖滨湿地位点健康状况较好,而西梁子湖湖滨湿地差异性较大,山坡湖南部湖湾和前江大湖北部位点健康状况良好,张桥湖湖滨湿地健康状况一般,评价较差的6个位点集中在宁港湖周围和前江大湖南部沿岸。底质和人类活动如水位调控、围网养殖、放牧等是影响梁子湖湖滨湿地植被生物完整性的主要原因。     

Effect of working time on environmental pressures: empirical evidence from EU-15, 1970–2010

There is growing interest in the correlation between working time and environmental pressures, but prior empirical studies mostly focused on static methodologies. This article used dynamic panel regression approaches to examine and compare the relationship among western, southern, and northern European countries over the period 1970–2010, and proved the existence of strongly significant relationships in all models. Furthermore, this article detected the relationship between working hours and environmental indicators (carbon emission and energy use) at different phases. We contribute to a further understanding of the environmental effects of the working time reduction policy by comparing the differences among various periods and country groups in a system generalized method of moments (GMM) dynamic framework.     

Roles of semivolatile and intermediate-volatility organic compounds in secondary organic aerosol formation and its implication: A review

Secondary organic aerosol (SOA) is a very important component of fine particulate matter (PM_2.5) in the atmosphere. However, the simulations of SOA, which could help to elucidate the detailed mechanism of SOA formation and quantify the roles of various precursors, remains unsatisfactory, as SOA levels are frequently underestimated. It has been found that the performance of SOA formation models can be significantly improved by incorporating the emission and evolution of semivolatile and intermediate-volatility organic compounds (S/IVOCs). In order to explore the roles of S/IVOCs in SOA formation, this study reviews some simulation models which could consider S/IVOCs for SOA formation as well as the development of emission inventories of S/IVOCs and S/IVOC modules for SOA formation. In addition, the future research directions for simulations of the effect of S/IVOCs on SOA formation are suggested.     

长江中下游河道与岸线演变特点

分析了长江中下游河道岸线变化的主要因素，它们分别是河岸崩塌，泥沙淤积及人类活动等，其中河岸崩塌是河道岸线演变的最主要原因。总的来说长江中下游干流河势是稳定的，但五个河段有各自演变特点和规律，其中宜昌－枝城段河道与河床比较稳定，岸线顺直，但葛洲坝和三峡水利枢纽建成后对河床的冲刷作用较大；荆江段是长江著名的河曲段，其冲淤变化较大；城陵矶至湖口段为节点和分汊河床组成，一般来说节点较为稳定，而分汊河床不太稳定，湖口至江阴河段岸线一般较为稳定，但弯道河床变化较大；河口段不但受江流作用影响，还受潮流与波浪等共同影响，所以河口河床演变迅速，主要表现为汊道主泓迁移摆动。     

Greenhouse gas emissions from MSW incineration in China: Impacts of waste characteristics and energy recovery

Determination of the amount of greenhouse gas (GHG) emitted during municipal solid waste incineration (MSWI) is complex because both contributions and savings of GHGs exist in the process. To identify the critical factors influencing GHG emissions from MSWI in China, a GHG accounting model was established and applied to six Chinese cities located in different regions. The results showed that MSWI in most of the cities was the source of GHGs, with emissions of 25–207 kg CO₂-eq t^?1 rw. Within all process stages, the emission of fossil CO₂ from the combustion of MSW was the main contributor (111–254 kg CO₂-eq t^?1 rw), while the substitution of electricity reduced the GHG emissions by 150–247 kg CO₂-eq t^?1 rw. By affecting the fossil carbon content and the lower heating value of the waste, the contents of plastic and food waste in the MSW were the critical factors influencing GHG emissions of MSWI. Decreasing food waste content in MSW by half will significantly reduce the GHG emissions from MSWI, and such a reduction will convert MSWI in Urumqi and Tianjin from GHG sources to GHG sinks. Comparison of the GHG emissions in the six Chinese cities with those in European countries revealed that higher energy recovery efficiency in Europe induced much greater reductions in GHG emissions. Recovering the excess heat after generation of electricity would be a good measure to convert MSWI in all the six cities evaluated herein into sinks of GHGs.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.