Diurnal and Seasonal Variations in Carbon Dioxide Exchange in Ecosystems in the Zhangye Oasis Area, Northwest China

<div><p>Quantifying carbon dioxide exchange and understanding the response of key environmental factors in various ecosystems are critical to understanding regional carbon budgets and ecosystem behaviors. For this study, CO₂ fluxes were measured in a variety of ecosystems with an eddy covariance observation matrix between June 2012 and September 2012 in the Zhangye oasis area of Northwest China. The results show distinct diurnal variations in the CO₂ fluxes in vegetable field, orchard, wetland, and maize cropland. Diurnal variations of CO₂ fluxes were not obvious, and their values approached zero in the sandy desert, desert steppe, and Gobi ecosystems. Additionally, daily variations in the Gross Primary Production (<i>GPP</i>), Ecosystem Respiration (<i>R_eco</i>) and Net Ecosystem Exchange (<i>NEE</i>) were not obvious in the sandy desert, desert steppe, and Gobi ecosystems. In contrast, the distributions of the <i>GPP</i>, <i>R_eco</i>, and <i>NEE</i> show significant daily variations, that are closely related to the development of vegetation in the maize, wetland, orchard, and vegetable field ecosystems. All of the ecosystems are characterized by their carbon absorption during the observation period. The ability to absorb CO₂ differed significantly among the tested ecosystems. We also used the Michaelis-Menten equation and exponential curve fitting methods to analyze the impact of Photosynthetically Active Radiation (<i>PAR</i>) on the daytime CO₂ flux and impact of air temperature on <i>R_eco</i> at night. The results show that <i>PAR</i> is the dominant factor in controlling photosynthesis with limited solar radiation, and daytime CO₂ assimilation increases rapidly with <i>PAR</i>. Additionally, the carbon assimilation rate was found to increase slowly with high solar radiation. The light response parameters changed with each growth stage for all of the vegetation types, and higher light response values were observed during months or stages when the plants grew quickly. Light saturation points are different for different species. Nighttime <i>R_eco</i> increases exponentially with air temperature. High Q₁₀ values were observed when the vegetation coverage was relatively low, and low Q₁₀ values occurred when the vegetables grew vigorously.</p></div

Daily variations in <i>NEE</i>, <i>R</i>_<i>eco</i> and <i>GPP</i> in different ecosystems.

<p>Daily variations in <i>NEE</i>, <i>R</i>_<i>eco</i> and <i>GPP</i> in different ecosystems.</p

The distribution of the eddy covariance in different ecosystems.

<p>The distribution of the eddy covariance in different ecosystems.</p

Diurnal variations of <i>NEE</i> in different ecosystems.

<p>Diurnal variations of <i>NEE</i> in different ecosystems.</p

Response of <i>NEE</i> to <i>PAR</i> in different ecosystems.

<p>Response of <i>NEE</i> to <i>PAR</i> in different ecosystems.</p

Maximum <i>GPP</i>, <i>R</i>_<i>eco</i>, and Minimum <i>NEE</i> for different ecosystems during the observation period (June 10—September 14, and, in wetland, June 26—September 14).

<p>Maximum <i>GPP</i>, <i>R</i>_<i>eco</i>, and Minimum <i>NEE</i> for different ecosystems during the observation period (June 10—September 14, and, in wetland, June 26—September 14).</p

Tailpipe emission characteristics of PM_2.5 from selected on-road China III and China IV diesel vehicles

<p>Eighteen China III and IV diesel vehicles, including light-duty diesel trucks (LDDTs), medium-duty diesel trucks (MDDTs), heavy-duty diesel trucks (HDDTs) and buses, were tested with real-world measurements using a portable emission measurement system (PEMS). The emission factors (EFs), chemical components and surface morphology of emitted particles from these vehicles were characterized. Measured features included organic carbon (OC), elemental carbon (EC), water soluble ions (WSIs) and trace elements of PM_2.5. The modelling system MOtor Vehicle Emission Simulator (MOVES) was also employed to estimate the PM_2.5 EFs from these vehicles. Carbonaceous content made up 35.8–110.8% of PM_2.5, the largest contribution of all the determined chemical components; WSIs and elements accounted for less than 10%. The average PM_2.5 EFs of MDDTs and HDDTs were 0.389 g·km⁻¹ and 0.115 g·km⁻¹, respectively, approximately one order of magnitude higher than that of LDDTs. The PM_2.5 EFs of China III buses were much lower than those of China III MDDTs and HDDTs, indicating that the inspection maintenance program (I/M) system was carried out effectively on public diesel vehicles. Moreover, the chemical composition of 9.2–56.2% of the PM_2.5 mass emitted from China IV diesel trucks could not be identified in the present study. It was possible this unidentified mass was particle bound water, but this hypothesis should be confirmed with further measurements. The SEM images of PM_2.5 samples presented a loose floc structure. In addition, the trends of variation of estimated PM_2.5 EFs derived from the MOVES simulation were essentially consistent with those of tested values.</p> <p>Copyright © 2018 American Association for Aerosol Research</p

Temporal dynamic patterns of modelled GPP generated with simulated daily LAI and FPAR together with ground based ones during the growing season of 2012.

<p>(a) croplands. (b) orchard. (c) vegetable field. (d) wetland. For modelled and ground-based values, error bars represent mean and maximum/minimum for GPP in a 10-day period.</p

Spatial distribution of field sampling sites.

<p>Spatial distribution of field sampling sites.</p

The chemical structures of flavone and LZ-207.

<p>(A) Chemical structure of the 15-carbon flavone backbone. (B) Chemical structure of LZ-207 (C₂₆H₃₂N₂O₆, MW = 468.5421).</p