Search

Abstract: Receptor models are useful tools to identify sources of a specific pollutant and to estimate the quantitative contributions of each source based on environmental data. This paper reports on similarities and differences in results achieved when testing three receptor models for estimating the sources of polycyclic aromatic hydrocarbons (PAHs) in soils from Huanghuai Plain, China. The three tested models are Principal Component Analysis with Multiple Linear Regression (PCA-MLR), Positive Matrix Factorization (PMF) and Unmix. Overall source contributions as well as modeled ∑PAHs concentrations compared well among models. All three models apportioned three common PAH sources: wood/biomass burning, fossil fuel combustion and traffic emission, which contributed on average 27.7%, 53.0% and 19.3% by PCA-MLR, 36.9%, 27.2% and 16.3% by PMF, and 47.8%, 21.1% and 18.3% by Unmix to the total sum of PAHs (∑PAHs), respectively. Moreover, the spatial evolution of the common sources were well correlated among models (r=0.83–0.99, p <0.001). In addition, the PMF and Unmix models allowed segregating an additional source from the fossil fuel combustion source, with 19.6% and 11.8% contributions to ∑PAHs, respectively. The current findings further validate that different receptor models provide divergent source profiles, which are mainly attributed to both the model itself and/or the underlying dataset. It is therefore generally recommended to apply multiple techniques to determine the source apportionment in order to minimize individual-method weaknesses and thereby to strengthen the conclusion. [Copyright &y& Elsevier]

Abstract: This paper uses nonparametric efficiency analysis technique to estimate the energy efficiency, potential emission reductions and marginal abatement costs of energy-related CO2 emissions in China. We employ a non-radial slacks-based data envelopment analysis (DEA) model for estimating the potential reductions and efficiency of CO2 emissions for China. The dual model of the slacks-based DEA model is then used to estimate the marginal abatement costs of CO2 emissions. An empirical study based on China’s panel data (2001–2010) is carried out and some policy implications are also discussed. [Copyright &y& Elsevier]

Abstract: An emission pre-processing tool is generally needed to transform a bulk annual emission inventory into gridded, temporal (monthly, weekly, and hourly), and speciated emissions in order to use complex air quality models such as the Community Multi-scale Air Quality (CMAQ) model to assess control strategies, forecast air quality, and investigate pollution formation and transport processes. To support the regional air quality modeling in the Pearl River Delta (PRD), we developed an emission pre-processing system, Sparse Matrix Operator Kernel Emissions-PRD (SMOKE-PRD), based on the U.S. Environmental Protection Agency (USEPA)/SMOKE model. This paper introduces the methods and procedures for adapting the SMOKE model to the PRD regional bulk emissions. These include the compilation of the PRD local source-class clarification codes, the incorporation of the PRD local emission inventory, and the updating of spatial, temporal, and chemical speciation information. The SMOKE-PRD system was evaluated, and a case study on ozone simulation was conducted to demonstrate the applicability of the SMOKE-PRD system. Results show that the model can properly simulate temporal variations, spatial patterns, and peak values of O3 concentrations in the PRD region, suggesting the SMOKE-PRD system was successfully localized and can be used to provide model-ready emissions for regional air quality modeling in the PRD region. This work can be extended for adapting the SMOKE model to process emissions for modeling use in other regions of China. [Copyright &y& Elsevier]

Abstract: Air pollutant emission inventory is an important input parameter for chemical transport models (CTMs). Since great uncertainties exist in the emission inventory, further improvements and refinements are required. In this paper, genetic algorithm (GA), a global search and optimization method, was applied to optimize the emission inventory for the Models-3/Community Multiscale Air Quality (CMAQ) model. An emission optimizing system based on GA was developed and embedded to the CMAQ through the design of several core modules, which implemented the basic functions such as emission adjusting, GA population initializing, CMAQ results evaluating and GA operating. Hypothetical and real-data experiments were respectively performed to examine the validity of GA for emission calibrating. GA showed good performance in both experiments and was always able to find the global minimum. The emission optimizing system was then used to calibrate seasonal PM10 emission inventories of Beijing. Results revealed that PM10 emission in Beijing was underestimated in 2002, an average of 62.74% higher adjustment factor should be imposed on the original emission in target months of different seasons. With the calibrated emission inventories, CMAQ model errors were decreased by 6.46% on average in different seasons. It was concluded that GA was a promising search technique in calibrating emission inputs for CTMs. [ABSTRACT FROM AUTHOR]

Abstract: Following model evaluation in part I, this part II paper focuses on the process analysis and chemical regime analysis for the formation of ozone (O3) and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM10) in China. The process analysis results show that horizontal transport is the main contributor to the accumulation of O3 in Jan., Apr., and Oct., and gas-phase chemistry and vertical transport contribute to the production and accumulation of O3 in Jul. Removal pathways of O3 include vertical and horizontal transport, gas-phase chemistry, and cloud processes, depending on locations and seasons. PM10 is mainly produced by primary emissions and aerosol processes and removed by horizontal transport. Cloud processes could either decrease or increase PM10 concentrations, depending on locations and seasons. Among all indicators examined, the ratio of provides the most robust indicator for O3 chemistry, indicating a VOC-limited O3 chemistry over most of the eastern China in Jan., NOx-limited in Jul., and either VOC- or NOx-limited in Apr. and Oct. O3 chemistry is NOx-limited in most central and western China and VOC-limited in major cities throughout the year. The adjusted gas ratio, AdjGR, indicates that PM formation in the eastern China is most sensitive to the emissions of SO2 and may be more sensitive to emission reductions in NOx than in NH3. These results are fairly consistent with the responses of O3 and PM2.5 to the reductions of their precursor emissions predicted from sensitivity simulations. A 50% reduction of NOx or AVOC emissions leads to a reduction of O3 over the eastern China. Unlike the reduction of emissions of SO2, NOx, and NH3 that leads to a decrease in PM10, a 50% reduction of AVOC emissions increases PM10 levels. Such results indicate the complexity of O3 and PM chemistry and a need for an integrated, region-specific emission control strategy with seasonal variations to effectively control both O3 and PM2.5 pollution in China. [Copyright &y& Elsevier]

Abstract: This paper describes a study of local biogenic volatile organic compounds (BVOC) emissions from the Hong Kong Special Administrative Region (HKSAR). An improved land cover and emission factor database was developed to estimate Hong Kong emissions using MEGAN, a BVOC emission model developed by . Field surveys of plant species composition and laboratory measurements of emission factors were combined with other data to improve existing land cover and emission factor data. The BVOC emissions from Hong Kong were calculated for 12 consecutive years from 1995 to 2006. For the year 2006, the total annual BVOC emissions were determined to be 12,400 metric tons or 9.82 × 109 g C (BVOC carbon). Isoprene emission accounts for 72%, monoterpene emissions account for 8%, and other VOCs emissions account for the remaining 20%. As expected, seasonal variation results in a higher emission in the summer and a lower emission in the winter, with emission predominantly in day time. A high emission of isoprene occurs for regions, such as Lowest Forest-NT North, dominated by broadleaf trees. The spatial variation of total BVOC is similar to the isoprene spatial variation due to its high contribution. The year to year variability in emissions due to weather was small over the twelve-year period (−1.4%, 2006 to 1995 trendline), but an increasing trend in the annual variation due to an increase in forest land cover can be observed (+7%, 2006 to 1995 trendline). The results of this study demonstrate the importance of accurate land cover inputs for biogenic emission models and indicate that land cover change should be considered for these models. [Copyright &y& Elsevier]

Abstract: In this paper, in contrast to the usual rough estimation, we present a model to simulate and evaluate the direct, indirect economic and environmental impacts of the implementation of building energy efficiency standards on Chinese economic system and environment by 12 indicators in two scenarios. Four indicators are used to evaluate the direct economic impact degree, five indicators are used to evaluate the direct environmental impact degree, three indicators are used to evaluate the indirect economic impact degree of 34 sectors and the whole Chinese economic system. This research makes it possible to link developments in the implementation of building energy efficiency standards with environmental and economic structure change. The most important finding is that the implementation of building energy efficiency standards can reduce a large amount of pollutants emissions and increase the GDP at the same time. [Copyright &y& Elsevier]

Abstract: This paper presents life-cycle-analysis (LCA) energy consumption (EC) and greenhouse gas (GHG) emissions of China’s current six biofuel pathways, which are: corn-derived ethanol (CE); cassava-derived ethanol (KE); sweet sorghum-derived ethanol (SE); soybean-derived bio-diesel (SB); jatropha fruit-derived bio-diesel (JB); and used cooking oil (UCO)-derived bio-diesel (UB). The tool utilized here is the WTW (Well-to-Wheels) module of Tsinghua-CA3EM model covering the entire lifecycle including: raw materials cultivation (or feedstock collection); fuel production; transportation and distribution; and application in automobile engines, compared with Conventional Petroleum-based gasoline and diesel Pathways (CPP). The results indicate: (1) the fossil energy inputs are about 1.0–1.5 times the energy contained in the fuel for the CE, SE and SB pathways, but 0.5–0.9 times for the KE, UB and JB pathways; (2) compared with CPP, the JB, KE and UB pathways can reduce both fossil fuel consumption and GHG emissions; the CE and SB pathways can only reduce fossil fuel consumption, but increase GHG emission; the SE pathway increases not only fossil fuel consumption but also GHG emission; and (3) the main factors inducing high EC and GHG emission levels include: high EC levels during the fuel production stage and high fertilizer application rates during the planting of raw feedstocks. Conclusions are that of the aforementioned biofuel pathways in China: (1) only the JB, KE and UB pathways have energy-saving merits as indicated by the LCA energy inputs and outputs; (2) compared with CPP, all but the SE pathway reduces fossil fuel consumption. However, the SB and CE pathway increase GHG emission; (3) all six displace petroleum by utilizing more coal; and (4) feedstock productivity levels must be increased, and there must be a reduction in fertilizer utilization and EC consumption during the cultivation and transportation stages in order to achieve the goals of energy balance and GHG emission reduction. [Copyright &y& Elsevier]