A2/O+MBR工艺运行效果与碳排放特征研究

对北京市通州区H再生水厂采用的A²/O+MBR工艺运行效果与不同环节碳排放特征进行研究.结果表明：2018年该再生水厂对BOD₅,COD_cr,NH₄⁺-N,TN和TP的平均去除率分别为97.3%,94.1%,98.6%,77.0%,96.2%;全厂碳排放总量和吨水碳排放量呈春夏季节逐渐降低,秋冬季节缓慢升高的特征,全厂综合吨水碳排放量约为2.26kgCO₂e/t.碳排放总量中能耗碳排放量占主要地位,CH₄,N₂O和物耗碳排放量占比较小;统计分析显示CH₄,能耗和物耗吨水碳排放量与BOD₅,TN进水浓度及BOD₅去除率显著相关;N₂O吨水碳排放量与TN与BOD₅进水浓度显著相关;直接,间接吨水碳排放量与水量无显著相关性.     

北京市典型城区餐饮业VOCs和PM2.5排放量估算

以北京市餐饮企业分布密度最大的西城区为案例区,通过对研究区域内餐饮企业进行实地污染物检测及排放活动水平调查,计算得到基于就餐人数、就餐时间、烹饪油用量和灶头数4种核算基准的餐饮业VOCs和PM_2.5排放因子,并利用排放因子法分别估算该区域在餐饮废气净化设备升级改造前后餐饮企业VOCs和PM_2.5年排放量.结果表明：本研究区域餐饮业废气净化设备升级改造前VOCs排放量范围为319.03~506.38t/a,改造后为92.14~109.89t/a;改造前PM_2.5排放量范围为166.55~211.09t/a,改造后为30.22~36.05t/a,排放量明显减少.餐饮业废气净化设备改造后VOCs和PM_2.5减排率分别为71%~82%和80%~86%,餐饮业废气净化设备升级改造减排效果良好.计算得到以街道为单元的餐饮源VOCs和PM_2.5排放强度范围分别为1.45~4.32t/km²和0.47~1.42t/km².通过PM_2.5实测浓度（小时值）数据分析,餐饮业废气净化设备升级改造前、后PM_2.5浓度平均减少了28.9%,最接近于用油量为核算基准的排放因子降低比例.     

Comprehensive and high-resolution emission inventory of atmospheric pollutants for the northernmost cities agglomeration of Harbin-Changchun, China: Implications for local atmospheric environment management

Using a bottom-up estimation method, a comprehensive, high-resolution emission inventory of gaseous and particulate atmospheric pollutants for multiple anthropogenic sectors with typical local sources has been developed for the Harbin-Changchun city agglomeration (HCA). The annual emissions for CO, NOx, SO₂, NH₃, VOC_S, PM_2.5, PM₁₀, BC and OC during 2017 in the HCA were estimated to be 5.82 Tg, 0.70 Tg, 0.34 Tg, 0.75 Tg, 0.81Tg, 0.67 Tg, 1.59 Tg, 0.12 Tg and 0.26 Tg, respectively. For PM₁₀ and SO₂, the emissions from industry processes were the dominant contributors representing 54.7% and 49.5%, respectively, of the total emissions, while 95.3% and 44.5% of the total NH₃ and NOx emissions, respectively, were from or associated with agricultural activities and transportation. Spatiotemporal distributions showed that most emissions (except NH₃) occurred in November to March and were concentrated in the central cities of Changchun and Harbin and the surrounding cities. Open burning of straw made an important contribution to PM_2.5 in the central regions of the northeastern plain during autumn and spring, while domestic coal combustion for heating purposes was significant with respect to SO₂ and PM_2.5 emissions during autumn and winter. Furthermore, based on Principal Component Analysis and Multivariable Linear Regression model, air temperature, relative humidity, electricity and energy consumption, and the urban and rural population were optimized to be representative indicators for rapidly assessing the magnitude of regional atmospheric pollutants in the HCA. Such indicators and equations were demonstrated to be useful for local atmospheric environment management.     

Primary and secondary organic aerosol in an urban/industrial site: Sources, health implications and the role of plastic enriched waste burning

PM10 samples were collected from an urban/industrial site nearby Athens, where uncontrolled burning activities occur. PAHs, monocarboxylic, dicarboxylic, hydroxycarboxylic and aromatic acids, tracers from BVOC oxidation, biomass burning tracers and bisphenol A were determined. PAH, monocarboxylic acids, biomass burning tracers and bisphenol A were increased during autumn/winter, while BSOA tracers, dicarboxylic- and hydroxycarboxylic acids during summer. Regarding aromatic acids, different sources and formation mechanisms were indicated as benzoic, phthalic and trimellitic acids were peaked during summer whereas p-toluic, isophthalic and terephthalic were more abundant during autumn/winter. The Benzo[a]pyrene-equivalent carcinogenic power, carcinogenic and mutagenic activities were calculated showing significant (p < 0.05) increases during the colder months. Palmitic, succinic and malic acids were the most abundant monocarboxylic, dicarboxylic and hydrocarboxylic acids during the entire sampling period. Isoprene oxidation was the most significant contributor to BSOA as the isoprene-SOA compounds were two times more abundant than the pinene-SOA (13.4 ± 12.3 and 6.1 ± 2.9 ng/m³, respectively). Ozone has significant impact on the formation of many studied compounds showing significant correlations with: isoprene-SOA (r = 0.77), hydrocarboxylic acids (r = 0.69), pinene-SOA (r = 0.63),dicarboxylic acids (r = 0.58), and the sum of phthalic, benzoic and trimellitic acids (r = 0.44). PCA demonstrated five factors that could explain sources including plastic enriched waste burning (30.8%), oxidation of unsaturated fatty acids (23.0%), vehicle missions and cooking (9.2%), biomass burning (7.7%) and oxidation of VOCs (5.8%). The results highlight the significant contribution of plastic waste uncontrolled burning to the overall air quality degradation.     

基于LCA的钢铁联合企业CO_2排放影响因素分析

钢铁企业是CO2排放大户,减少吨钢CO2排放是钢铁企业节约能源、保护环境、走可持续发展道路的必然要求.本研究旨在对钢铁企业产品生命周期清单研究的基础上,识别钢铁企业CO2排放的主要影响因素,提出针对性的减排建议.以某钢铁联合企业的产品生命周期清单模型为平台,同时利用TornadoChart工具,计算得到对企业CO2排放影响较大的因素,然后提出了相应的减排措施.结果表明,转炉流程对于钢铁企业的影响要大于电炉流程;对该企业CO2排放有重大影响和相关影响的因素有:高炉煤气(BFG)的CO2排放系数、连铸坯的钢水单耗、热轧的板坯单耗、转炉的铁水比.减少钢铁联合企业CO2排放的有效措施是采取捕集BFG中的CO2、降低转炉的铁水比、加强副产煤气的回收以及优化企业的产品生产结构.     

The regional economic impact of reducing greenhouse gas emissions: Western Australia

This study analyses the general-equilibrium impacts of an international climate change response policy on the economy of Western Australia (WA), one of the most mining-based and energy-intensive states of Australia. It finds that emissions would fall by up to 11% from the base level in WA. However, such environmental benefits emanate at some costs to the state economy; in terms of foregone gross state product, the costs are up to 3% of the base level. Indeed, the actual costs and benefits depend on the precise design of the climate change response policy as well as on the other policies within which it operates. For example, when emission quota permits are sold to industries and no tradeable carbon credits (i.e. credits for the carbon sequestrated in Kyoto forests) are granted, emissions decline by about 8% and GSP falls by about 3% of the base levels. If carbon credits are tradeable, however, the environmental benefits could be increased and the GSP cost could be reduced substantially. Also, the reduced economic activity caused by emission abatement results in a modest fall in net government revenue, despite the additional revenue from permit sales in some cases. Accordingly, government’s fiscal package surrounding the emission permits would influence the emission abatement impacts on the economy. With regard to the effects on the structure of the state economy, the oil and gas industry suffers only a slight contraction but the energy-supplying sector as a whole contracts substantially. It is therefore not surprising that the impacts on the WA economy of curbing emissions by energy and transport industries alone are quite significant when compared to those resulted from all industries’ compliance with the abatement scheme. It needs to be noted that the model projections analysed in the paper are based on simplifying assumptions and tentative scenarios, and hence should be viewed with caution and not be understood as unconditional forecasts.     

区域高时空分辨率VOC天然源排放清单的建立

将中尺度气象模式MM5应用于估算VOC天然源排放的研究,建立了高时空分辨率VOC天然源排放清单的估算方法.根据方法需要,确定了我国部分树木排放异戊二烯和萜烯的标准排放因子,各植被类型排放各种VOC的标准排放因子,以及各植被类型季节平均的叶生物量密度.应用该方法估算了华南地区满足区域空气质量数值模拟要求的高时空分辨率VOC天然源排放清单.结果表明,华南地区夏季典型日的VOC天然源排放总量约1.12×10⁴t,VOC排放速率具有明显的时空分布,其中地理分布取决于植被类型及其分布,日变化规律则依赖于太阳辐射和温度的高低.并讨论了VOC天然源排放估算过程中误差的来源     

Urban expansion and its contribution to the regional carbon emissions: Using the model based on the population density distribution

The method is used for calculating regional urban area dynamics and the resulting carbon emissions (from the land-conversion) for the period of 1980 till 2050 for the eight world regions. This approach is based on the fact that the spatial distribution of population density is close to the two-parametric Γ-distribution [Kendall, M.G., Stuart, A., 1958. The Advanced Theory of Statistics, vol. 1.2. Academic Press, New York; Vaughn, R., 1987. Urban Spatial Traffic Patterns, Pion, London]. The developed model provides us with the scenario of urbanisation, based on which the regional and world dynamics of carbon emissions and export from cities, and the annual total urban carbon balance are estimated. According to our estimations, world annual emissions of carbon as a result of urbanisation increase up to 1.25 GtC in 2005 and begin to decrease afterwards. If we compare the emission maximum with the annual emission caused by deforestation, 1.36 GtC per year, then we can say that the role of urbanised territories (UT) in the global carbon balance is of a comparable magnitude. Regarding the world annual export of carbon from UT, we observe its monotonous growth by three times, reaching 505 MtC. The latter, is comparable to the amount of carbon transported by rivers into the ocean (196–537 MtC). The current model shows that urbanisation is inhibited in the interval 2020–2030, and by 2050 the growth of urbanised areas would almost stop. Hence, the total balance, being almost constant until 2000, then starts to decrease at an almost constant rate. By the end of the XXI century, the total carbon balance will be equal to zero, with the exchange flows fully balanced, and may even be negative, with the system beginning to take up carbon from the atmosphere, i.e., becomes a “sink”. The regional dynamics is somewhat more complex, i.e., some regions, like China, Asia and Pacific are being active sources of Carbon through the studied period, while others are changing from source to sink or continue to be neutral in respect the GCC.     

东北三省农田生态系统碳排放时空分异特征及驱动因素研究

根据2000—2014年东北三省碳排放的相关数据,结合空间探索性分析及地理加权回归等模型方法,对研究区农田生态系统碳排放量的空间集聚性、差异性及其重要驱动因素进行研究.结果表明:东北三省农田生态系统碳排放量存在比较显著的全局空间正相关,自相关性在整体上表现出逐渐增强的趋势,到2014年全局Moran's I指数达到最高值0.3395.在局部空间相关关系上,东北三省农田生态系统碳排放量的高-高区域集中在黑龙江省和吉林省,低-低地区主要集中在辽宁省,表现出不平衡的发展格局.人均GDP对农田生态系统碳排放有负效应,总人口数对农田生态系统碳排放的影响从正效应转变为负效应,化肥施用对农田生态系统碳排放影响程度的空间分布格局发生了较大变化,代表生产技术水平和能源消耗的农业化肥施用量和农业机械总动力因素对农田生态系统碳排放的影响较大,东北三省农田生态系统碳排放和农业机械总动力相关程度有逐渐趋同的趋势.     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.