Yuanchao Hu

Iodine uptake by spinach (Spinacia oleracea L.) plants grown in solution culture: effects of iodine species and solution concentrations

A hydroponic experiment was carried out to investigate the effects of iodine species and solution concentrations on iodine uptake by spinach (Spinacia oleracea L.). Five iodine concentrations (0, 1, 10, 50 and 100 microM) for iodate (IO(3)(-)) and iodide (I(-)) were used. Results show that higher concentrations of I(-) (> or =10 microM) had some detrimental effect on plant growth, while IO(3)(-) had little effect on the biomass production of spinach plants. Increases in iodine concentration in the growth solution significantly enhanced I concentrations in plant tissues. The detrimental effect of I(-) on plant growth was probably due to the excessively high accumulation of I in plant tissues. The solution-to-spinach leaf transfer factors (TF(leaf), fresh weight basis) for plants treated with iodide were between 14.2 and 20.7 at different solution concentrations of iodide; TF(leaf) for plants treated with iodate decreased gradually from 23.7 to 2.2 with increasing solution concentrations of iodate. The distribution coefficients (DCs) of I between leaves and roots were constantly higher for plants treated with iodate than those treated with iodide. DCs for plants treated with iodide increased with increasing solution concentrations of iodide, while DCs for plants treated with iodate (around 5.5) were similar across the range of solution concentrations of iodate used in this experiment. The implications of iodine accumulation in leafy vegetables in human iodine nutrition are also discussed.

Arsenate Causes Differential Acute Toxicity to Two P-deprived Genotypes of Rice Seedlings (Oryza sativa L.)

Significant genotypic difference in response to arsenate toxicity in rice (Oryza sativa) was investigated in root elongation, arsenate uptake kinetics, physiological and biochemical response and arsenic (As) speciation. Uptake kinetics data showed that P-deprived genotype 94D-54 had a little higher As uptake than P-deprived 94D-64, but the difference was not large enough to cause acute toxicity in P-deprived 94D-54. There was no difference in tissue P concentrations between the two genotypes under P deficient conditions. In addition, arsenic speciation in plant tissues (using high performance liquid chromatography-inductively coupled plasma mass spectrometry) was not different between P pretreatments and between genotypes. P-deprived genotype 94D-54 suffered much higher stress induced by arsenate toxicity than P-deprived genotype 94D-64, in terms of lipid peroxidation, tissue H2O2 concentrations and exosmosis of K, P and As. However, P-deprived 94D-54 also had higher overproduction of enzymatic antioxidants (with higher GPX, SOD, CAT) and NPT (non-protein thiols) than P-deprived 94D-64. It appeared that, the higher sensitivity of P-deprived 94D-54 to arsenate toxicity might cause the overproduction of NPT, thus leading to the depletion of GSH and to the accumulation of H2O2. The differential sensitivity of the two genotypes has major implications for breeding rice for As affected paddy soil.

Tracking urban carbon footprints from production and consumption perspectives

Cities are hotspots of socio-economic activities and greenhouse gas emissions. The aim of this study was to extend the research range of the urban carbon footprint (CF) to cover emissions embodied in products traded among regions and intra-city sectors. Using Xiamen City as a study case, the total urban-related emissions were evaluated, and the carbon flows among regions and intra-city sectors were tracked. Then five urban CF accountings were evaluated, including purely geographic accounting (PGA), community-wide infrastructure footprint (CIF), and consumption-based footprint (CBF) methods, as well as the newly defined production-based footprint (PBF) and purely production footprint (PPF). Research results show that the total urban-related emissions of Xiamen City in 2010 were 55.2 Mt CO2e/y, of which total carbon flow among regions or intra-city sectors accounted for 53.7 Mt CO2e/y. Within the total carbon flow, import and export respectively accounted for 59 and 65%, highlighting the importance of emissions embodied in trade. By regional trade balance, North America and Europe were the largest net carbon exported-to regions, and Mainland China and Taiwan the largest net carbon imported-from regions. Among intra-sector carbon flows, manufacturing was the largest emission-consuming sector of the total urban carbon flow, accounting for 77.4, and 98% of carbon export was through industrial products trade. By the PBF, PPF, CIF, PGA and CBF methods, the urban CFs were respectively 53.7 Mt CO2e/y, 44.8 Mt CO2e/y, 28.4 Mt CO2e/y, 23.7 Mt CO2e/y, and 19.0 Mt CO2e/y, so all of the other four CFs were higher than the CBF. All of these results indicate that urban carbon mitigation must consider the supply chain management of imported goods, the production efficiency within the city, the consumption patterns of urban consumers, and the responsibility of the ultimate consumers outside the city.

Measuring Urban Carbon Footprint from Carbon Flows in the Global Supply Chain.

A global multiregional input-output (MRIO) model was built for eight Chinese cities to track their carbon flows. For in-depth understanding of urban carbon footprint from the perspectives of production, consumption, and trade balance, four kinds of footprints and four redefined measurement indicators were calculated. From the global supply chain, urban carbon inflows from Mainland China were larger than outflows, while the carbon outflows to European, principal North American countries and East Asia were much larger than inflows. With the rapid urbanization of China, Construction was the largest consumer and Utilities was the largest producer. Cities with higher consumption (such as Dalian, Tianjin, Shanghai, and Beijing) should change their consumption patterns, while cities with lower production efficiency (such as Dalian, Shanghai, Ningbo, and Chongqing) should improve their technology. The cities of net carbon consumption tended to transfer carbon emissions out of them by trading in carbon-intensive products, while the cities of net carbon production tended to produce carbon-intensive products for nonlocal consumers. Our results indicated that urban carbon abatement requires not only rational consumption and industrial symbiosis at the city level, but also tighter collaboration along all stages of the global supply chain.

Factor decomposition of Chinese GHG emission intensity based on the Logarithmic Mean Divisia Index method

Substantive decomposition research focuses on the energy-related carbon emissions from industrial sectors rather than from the household sector or non-energy-related activities. We extended the application of the Logarithmic Mean Divisia Index (LMDI) method to a comprehensive analysis of GHG emission intensity [GHG/unit of gross domestic product (GDP)] related to the industrial and household sectors, and to their energy-related and non-energy-related activities. Chinese carbon intensity was decomposed and analyzed by the LMDI method for the latest three 5-year plans (9th FYP, 10th FYP and 11th FYP), from 1996 to 2010. Results show that Chinese GHG emission intensity has experienced an unconscious reduction stage, an unconscious increasing stage and a conscious reduction stage, respectively, during the three FYPs. Industrial energy intensity had the dominant effect on GHG emission intensity reduction among all coefficients in the three periods. However, the non-energy-related activities cannot be ignored; they had an average 12% effect on GHG emission intensity reduction during the three periods. The household sector averaged about a 10% reduction effect. Looking forward to the 12th FYP, there are still huge challenges to achieving the energy-saving and carbon-reduction goals, due to the opposing effects of national urbanization and eco-civilization construction strategies.

Greenhouse gas emissions from key infrastructure sectors in larger and smaller Chinese cities: method development and benchmarking

ABSTRACT With massive urbanization and infrastructure investments occurring in China, understanding GHG emissions from infrastructure use in small and large Chinese cities with different administrative levels is important for building future low-carbon cities. This paper identifies diverse data sources to assess GHG emission from community-wide infrastructure footprints (CIF) in four Chinese cities of varying population (1 to 20 million people) and administrative levels: Yixing, Qinhuangdao, Xiamen and Beijing. CIF addresses seven infrastructure sectors providing energy (fuels/coal), electricity, water supply and wastewater treatment, transportation, municipal waste management, construction materials, and food to support urban activities. Industrial energy use dominates the infrastructure GHG CIF in all four cities, ranging from 76% of total CIF in Yixing to 30% in Beijing, followed by residential energy use (6–13%), transportation (4–12%), commercial energy use (2–25%), food (6–11%), cement use (3–8%) and water (about 1%), thereby identifying priorities for low-carbon infrastructure development. Trans-boundary footprint contributions ranged from 31% (Beijing) to 8% (Qinhuangdao), indicating that supply chains to cities are important. GHGs from energy use are dominated by electricity (35–45%) and non-electricity coal use (30–50%). The authors demonstrate that disaggregated infrastructure use-efficiency metrics in each infrastructure sector provide useful baseline performance data for comparing diverse cities.