污水生物处理实际工艺中氧化亚氮的释放：现状与挑战

介绍了污水生物处理过程中N2O的产生途径,重点分析了污水厂典型脱氮工艺的N2O释放差异及其原因,提出了城市污水脱氮处理过程N2O减排的具体措施,并估算出全国城镇污水处理厂2011年N2O释放总量约为1.26×109g(以N计),对今后关于城市污水脱氮处理过程N2O产生及减排的研究趋势进行了评估.     

碳排放现状及驱动因素分解实证分析研究——以东莞市为例

根据IPCC碳排放计算指南核算东莞市2005年-2011年期间能源消费的碳排放量,并进行现状分析和采用对数平均权重分解法（LMDI）因素分解分析.研究结果表明：碳排放总量以5.8％速度增长,而碳排放强度以5.8％速度递减;煤是碳排放主源,但所占比重逐年下降;工业碳排放量比重最大,但是增速减慢;交通业、服务业和居民生活碳排放量及所占比重逐年增加;经济规模的扩大是拉动东莞市人均碳排放的决定因素,累计效应远高于能源效率和能源结构对碳减排影响.     

从碳排放权交易角度谈治理兰州市大气污染的应用研究

随着城市的发展,环境污染问题日益突出,碳排放权交易作为《京都议定书》认定的碳交易机制,在解决环境污染问题上发挥了重要作用。在分析配额型碳交易在美国的成功应用的基础上,针对兰州市的污染现状,构建兰州市碳排放权交易制度来治理大气污染：核定兰州市大气环境容量,确定总量控制目标;确定交易单位;确立碳排放权初始分配机制;制定交易规则,建立监管机构;政府监管并进行相应的惩罚。     

浅谈黑龙江及乌苏里江流域废水中污染物排放特征

以跨界流域黑龙江和乌苏里江为研究对象,通过合理的流域断面设置,对流域废水中的污染物及农药残留进行分析测定,通过监测结果为以后的污染防治提供依据。     

京津冀地区主要排放源减排对PM2.5污染改善贡献评估

研究选取2012年1月和7月作为冬夏两季代表时段,利用CMAQ/2D-VBS模型分析了冬夏两季京津冀地区主要排放源减排30%对改善区域PM_(2.5)污染的效果.结果表明,工业源对PM_(2.5)污染的贡献最大,其次是民用源,但工业源单位减排量贡献低于民用源,交通源和电厂源的整体贡献和单位减排量贡献均较小.工业部门内贡献最大的为钢铁冶金行业,其次是水泥、工业锅炉、炼焦、石灰砖瓦和化工行业.与各部门各物种排放量的比较反映出各排放源贡献大小与其一次PM_(2.5)排放水平高度相关.因京津冀地区冬季NO_x减排对PM_(2.5)形成的促进作用,以及冬季较弱的大气垂直扩散作用,各排放源夏季减排比冬季普遍更有效,交通源、电厂源以及工业源中的水泥、工业锅炉和石灰砖瓦行业夏季减排效果相比冬季优势明显.民用源由于采暖季排放较高而冬季贡献更明显,农业源因秸秆开放燃烧量大,冬季单位减排量贡献十分显著.从同等幅度减排考虑,应将工业源作为控制重点,优先控制其一次PM_(2.5)排放,在部门内进一步重点控制钢铁冶金行业的NO_x和SO_2排放、水泥行业的夏季NO_x排放以及炼焦行业的SO_2和NMVOC排放.民用源排放应着重在冬季采暖期控制.     

基于化石能源消耗的重庆市二氧化碳排放峰值预测

首先利用重庆市能源平衡表,采用IPCC方法 1对重庆市1997—2012年的碳排放进行核算;其次依据重庆市经济社会发展状况,通过LMDI因素分解法将影响碳排放的因素分解为:人口、人均GDP、产业结构、能源结构、能源强度和碳排放系数;然后利用扩展的重庆市STIRPAT碳排放模型,在9个情景模式下对2013—2050年重庆市碳排放进行预测;最后对比分析了各情景下的峰值大小及出现时间.研究发现:基准模式下的重庆市碳排放在2035年出现32135.38万t的峰值;提高能源利用技术、增加清洁能源使用比例和大力发展第三产业,能在不降低经济发展的情况下有效降低碳排放;消极因素中的第二产业占比下降比碳排放强度下降对碳排放的抑制作用更加明显;积极因素对碳排放峰值的影响比消极因素更有效.     

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.     

Spatial & temporal variations of PM10 and particle number concentrations in urban air

The size of particles in urban air varies over four orders of magnitude (from 0.001 μm to 10 μm in diameter). In many cities only particle mass concentrations (PM10, i.e. particles <10 μm diameter) is measured. In this paper we analyze how differences in emissions, background concentrations and meteorology affect the temporal and spatial distribution of PM10 and total particle number concentrations (PNC) based on measurements and dispersion modeling in Stockholm, Sweden. PNC at densely trafficked kerbside locations are dominated by ultrafine particles (<0.1 μm diameter) due to vehicle exhaust emissions as verified by high correlation with NOx. But PNC contribute only marginally to PM10, due to the small size of exhaust particles. Instead wear of the road surface is an important factor for the highest PM10 concentrations observed. In Stockholm, road wear increases drastically due to the use of studded tires and traction sand on streets during winter; up to 90% of the locally emitted PM10 may be due to road abrasion. PM10 emissions and concentrations, but not PNC, at kerbside are controlled by road moisture. Annual mean urban background PM10 levels are relatively uniformly distributed over the city, due to the importance of long range transport. For PNC local sources often dominate the concentrations resulting in large temporal and spatial gradients in the concentrations. Despite these differences in the origin of PM10 and PNC, the spatial gradients of annual mean concentrations due to local sources are of equal magnitude due to the common source, namely traffic. Thus, people in different areas experiencing a factor of 2 different annual PM10 exposure due to local sources will also experience a factor of 2 different exposure in terms of PNC. This implies that health impact studies based solely on spatial differences in annual exposure to PM10 may not separate differences in health effects due to ultrafine and coarse particles. On the other hand, health effect assessments based on time series exposure analysis of PM10 and PNC, should be able to observe differences in health effects of ultrafine particles versus coarse particles.     

A study on the factor market distortion and the carbon emission scale effect of two-way FDI

Based on the data of 30 Chinese provinces for the period from 2004 to 2015, this paper expounds the carbon emissions effect of two-way foreign direct investment (FDI) from the perspective of scale effect and factor market distortions. This study uses Kaya identity to decompose carbon emission and construct simultaneous equations model to empirically examine the factor market distortion and the carbon emission scale effect of two-way FDI. The results show that the inward foreign direct investment (IFDI) increase regional carbon emission through scale effect and also exacerbates factor market distortion in China, whereas the outward FDI trends reduce carbon emission and reduces factor market distortions in China. The study also shows that human capital, research and development (R&D), trade openness, and capital accumulation are important determinants of two-way FDI. Therefore, the study proposes that IFDI policies should focus on acquiring green technologies. In addition, the domestic enterprises should be encouraged to participate in global business.     

Influencing climate change regulations: examining responses from large-scale firms

Recent climate change projections and a push towards a universal agreement on carbon emission reductions suggest that firms will need to respond to future regulatory changes. This paper employs an influencing strategies lens to examine how large-scale firms might respond to future climate change regulations. The study uses a structured qualitative methodology to explore and explicate the strategic responses from 21 international firms to the proposed emissions trading scheme outlined in Australia's Garnaut Climate Change Review. The results of the analysis show that firms can use pre-emptive influencing strategies in attempts to shape and mould regulatory design parameters, secure high levels of transitional economic support, and shift the balance of public policies and expenditure. Complementary defensive strategies may also target policy makers and regulators with some of the potential negative consequences of the new regulations.