Impact of demographic dynamics on CO_2 emissions in Sichuan,China

Global climate change is one of the major environmental issues faced by humans.Existing evidence indicates that the anthropogenic push for a rise in the atmospheric concentration of greenhouse gases(GHGs)(particularly CO_2)has been a primary cause for global warming.Aside from economic and teclinological factors,demographic dynamics(including human consumption in a broad demographic sense)has been a major driver for CO_2 emissions.In this paper,we performed both nonlinear regression analysis(based on the STIRPAT model)and gray correlation degree analysis(based on gray system theory)on the impact of demographic dynamics on CO_2 emissions.Our results reveal that CO_2 emissions are positively correlated with population size and GDP per capita and negatively correlated with energy intensity.We also show that gray correlation degree with CO_2 emissions for five variables(i.e.,household consumption,urbanization rate,household size,population aging rate,population size)varies substantially:household consumptionurbanization ratehousehold sizepopulation aging ratepopulation size,with household consumption being the highest,and population size the lowest.To mitigate the impact of demographic dynamics on CO_2 emissions,it is of vital significance to nurture people's awareness of sustainable consumption and to adhere to current population control policies.     

Effects of EGR on performance and emissions of a diesel engine fuelled with balanites aegyptiaca/diesel blends

In this study, balanites Aegyptiaca (L.) Del biodiesel was blended in proportions of 10% and 20% on the volume basis with diesel fuel and tested in a single cylinder, VCR diesel engine under measured load conditions with varied EGR rates (0, 10 and 20%). The results showed that B10 and B20 blends shown a significant reduction rate in terms of NO_x emissions that were familiar with biodiesel blends. At peak load conditions, BTE increased slightly for test fuel blends compared with pure diesel fuel while the BSFC rate and EGT suffered from increasing and decreasing nature with respect to blending percentage. From the emissions point of view, with the increase in blends percentage, a significant reduction rate is observed in terms of CO and HC concentrations (up to 12.34 and 17.5%, respectively) while NOx emissions decreased at peak load conditions (up to 24.34%). HC and CO emissions decreased with increase in blends percentage. However, lower levels of NO_x and EGT (up to 21.37 and 8.47%, respectively) and the average increase in terms of BTE and BSFC (up to 2.83 and 2.9%, respectively) can be realised with B20 test fuel blend under 20% EGR rate.     

The Clean Development Mechanism and Sustainable Development in China''''s Electricity Sector

1 INTRODUCTIONEnergy and environmental issues in China have receivedsignificant attention in both the peer-reviewed literatureand in international energy and environmental policymaking in the last number of years. China's coal dominatedenergy consumption results in significant regional pollutionproblems, most notably acid rain that affects nearly 1/3rdof China's landmass and air pollution that plagues manyof its major cities. China now ranks as the top emitterof sulphur dioxide (SO2) pol…     

中国碳排放的因素分解模型及实证分析:1995-2004

能源消费是碳排放的主要来源。随着中国经济的快速发展,能源消费的急剧增长以及以煤为主的能源结构在短期内很难改变,因此,碳排放不可避免地会出现一定幅度的增加。本文基于碳排放量的基本等式,采用对数平均权重Divisia分解法（Logarithmic mean weight Divisia method,LMD）,建立中国人均碳排放的因素分解模型,定量分析了1995-2004年间,能源结构、能源效率和经济发展等因素的变化对中国人均碳排放的影响,结果显示经济发展对拉动中国人均碳排放的贡献率呈指数增长,而能源效率和能源结构对抑制中国人均碳排放的贡献率都呈倒“U”。这说明能源效率对抑制中国碳排放的作用在减弱,以煤为主的能源结构未发生根本性变化,能源效率和能源结构的抑制作用难以抵销由经济发展拉动的中国碳排放量增长。     

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.     

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.     

Methane and nitrous oxide emissions from a subtropical coastal embayment (Moreton Bay, Australia)

Surface water methane (CH₄) and nitrous oxide (N₂O) concentrations and fluxes were investigated in two subtropical coastal embayments (Bramble Bay and Deception Bay, which are part of the greater Moreton Bay, Australia). Measurements were done at 23 stations in seven campaigns covering different seasons during 2010-2012. Water-air fluxes were estimated using the Thin Boundary Layer approach with a combination of wind and currents-based models for the estimation of the gas transfer velocities. The two bays were strong sources of both CH₄ and N₂O with no significant differences in the degree of saturation of both gases between them during all measurement campaigns. Both CH₄ and N₂O concentrations had strong temporal but minimal spatial variability in both bays. During the seven seasons, CH₄ varied between 500% and 4000% saturation while N₂O varied between 128 and 255% in the two bays. Average seasonal CH₄ fluxes for the two bays varied between 0.5 ± 0.2 and 6.0 ± 1.5 mg CH₄/(m²·day) while N₂O varied between 0.4 ± 0.1 and 1.6 ± 0.6 mg N₂O/(m²·day). Weighted emissions (t CO₂-e) were 63%-90% N₂O dominated implying that a reduction in N₂O inputs and/or nitrogen availability in the bays may significantly reduce the bays' greenhouse gas (GHG) budget. Emissions data for tropical and subtropical systems is still scarce. This work found subtropical bays to be significant aquatic sources of both CH₄ and N₂O and puts the estimated fluxes into the global context with measurements done from other climatic regions.     

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.     

船舶排放及不确定性对中国空气质量的影响

船舶排放是我国沿海地区重要的人为排放源,但现有的船舶排放评估研究大多只关注区域尺度的影响分析,而且忽视了排放清单的不确定性,这在一定程度上削弱了评估结果的可靠性.为此,本文利用WRF-SMOKE-CAMQ空气质量模型,定量评估了船舶排放及其不确定性对我国七大沿海港口城市夏季空气质量的影响,结果表明：船舶排放对我国主要沿海港口城市的SO₂、NO_x和PM_2.5浓度贡献范围分别为16.5%~62.5%、21.9%~72.9%和5.9%~26.0%,尤其对宁波、青岛和深圳等港口城市空气质量的影响显著,主要是由于港口较高的船舶排放以及气象传输两方面原因造成的;如果考虑船舶排放清单的总量不确定性,船舶排放对沿海港口城市夏季SO₂、NO_x和PM_2.5的影响分别呈现1.0~3.1,2.1~5.5,0.3~0.9μg/m³的波动;考虑船舶排放清单的时空分配不确定性,船舶排放对沿海港口城市夏季SO₂、NO_x和PM_2.5的影响分别呈现1.9~15.7,5.1~29.3,0.6~2.5μg/m³的波动.可见,船舶排放清单的不确定性对沿海城市船舶排放贡献影响量化有明显的影响.所以在评估船舶排放对港口城市空气质量的影响时,要考虑船舶排放清单的不确定性,尤其是时空分配的不确定性.而合理的时空分配能够提高船舶排放清单的质量和对沿海空气质量模拟的准确性.     

含菌气溶胶扩散对人群的潜在影响风险

为分析生物气溶胶释放对人群潜在影响风险的情况,利用CALPUFF模型定量模拟了2019年7月24~8月20日中牧兰州生物药厂含菌气溶胶扩散、浓度空间分布、对人群潜在健康风险,并结合公开报道的检测数据开展验证.结果显示：生物药厂的含菌气溶胶排放源附近高值区主要集中于厂区四周,影响范围主要以厂区为中心,并向四周逐渐扩散;检测结果中兰州兽研所1#,兰州大学2#地区健康风险比例41.49：1,在模拟的相对风险大小的误差区间（36.15±8.48）范围内,说明本研究含菌气溶胶对人群潜在影响风险的模拟结果可信.