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We apply the regional chemistry-transport model WRF-Chem to investigate the air pollution characteristics in three Chinese metropolitan areas (Beijing, Shanghai and Guangzhou) and assess the model performance in wintertime (January 2010) and summertime (July 2010) conditions. Three simulations utilizing the HTAPv2, REASv2 and MACCity anthropogenic emission inventories are conducted and compared with satellite and ground-based measurements to assess the sensitivity of the model predictions to anthropogenic emissions. Model-predicted surface meteorological fields are overall in good agreement with surface observations. However, the model tends to overestimate maximum surface wind speed, a feature also found in previous WRF-Chem modelling studies. Large discrepancies between the three emission inventories are found, specifically in the spatial distribution and the magnitude of the emissions (e.g. over 98%, 86% and 85% differences in some regions for carbon monoxide (CO), nitrogen oxide (NO) and organic carbon (OC) emissions, respectively). As a result, we find large differences between the simulations. When compared to satellite and surface observations, the HTAPv2-and REASv2-based simulations better reproduce the magnitude and spatial patterns of CO total columns and NO2 tropospheric columns derived from MOPITTv6 and GOME2 satellite observations, respectively. The simulations satisfactorily reproduce the air pollution characteristics in January 2010 as observed at surface monitoring stations in Beijing and Shanghai. The HTAPv2-based simulation better captures the pollution episode that occurred in Beijing in mid-January 2010, which is found to be related to a combination of different meteorological factors that led to the build-up of pollution. The high photochemical activity and convective turbulence in July 2010, in addition to differences in the emissions used, led to more pronounced differences between the simulations and lower statistical skills in particular for trace gases. This study shows that a considerable part of uncertainties in air quality model predictions for China can be attributed to uncertainties in current anthropogenic emission inventories. It highlights the need for more accurate and highly resolved emissions in order to improve the accuracy of model predictions. However, this study reveals that in some cases, model-observation discrepancies cannot be attributed only to inaccuracies in the emissions. For example, we found that regardless of the adopted emissions, all of the simulations fail to capture the temporal variability of particulate matter in Guangzhou during January 2010, indicating that factors other than emissions have a considerable influence on the atmospheric composition in this region. This work shows that inaccuracies in the predicted meteorological parameters (e.g. wind speed/direction, relative humidity, etc.) significantly affect the model performance, as found for example in the model predictions for Shanghai for July 2010, which show high and abrupt increases of NOx and particulates due to rapid decreases in wind speed in the model.

International audience; Increasing use of emerging per- and polyfluoroalkyl substances (PFASs) has caused extensive concerns around the world. Effective detection methods to trace their pollution characteristics and environmental behaviors in complex soil-crop systems are urgently needed. In this study, a reliable and matrix effect (ME)-free method was developed for simultaneous determination of 14 legacy and emerging PFASs, including perfluorooctanoic acid, perfluorooctane sulfonate, 6 hydrogenous PFASs, 3 chlorinated PFASs, and 3 hexafluoropropylene oxide homologues, in 6 crop (the edible parts) and 5 soil matrices using ultrasonic extraction combined with solid-phase extraction and ultraperformance liquid chromatography-mass spectrometry (MS)/MS. The varieties of extractants and cleanup cartridges, the dosage of ammonia hydroxide, and the ME were studied to obtain an optimal pretreatment procedure. The developed method had high sensitivity and accuracy with satisfactory method detection limits (2.40-83.03 pg/g dry weight) and recoveries (72-117%) of all target analytes in matrices at five concentrations, that is, 0.1, 1, 10, 100, and 1000 ng/g. In addition, the ME of this method (0.82-1.15) was negligible for all PFASs, even considering 11 different matrices. The successful application of the ME-free method to simultaneously determine the legacy and emerging PFASs in crop and soil samples has demonstrated its excellent practicability for monitoring emerging PFASs in soil-crop systems.

The well-documented energy balance dynamics within forest ecosystems are poorly implemented in studies of the biophysical effects of forests. This results in limitations to the accurate quantification of forest cooling/warming on local air temperature. Taking into consideration the forest air space, this study proposes a three-layered (canopy, forest air space and soil [CAS]) land surface energy balance model to simulate air temperature within forest spaces (Taf) and subsequently to evaluate its biophysical effects on forest cooling/warming, i.e., the air temperature gradient (∆Ta) between the Taf and air temperature of open spaces (Tao) (∆Ta = Taf − Tao). We test the model using field data for 23 sites across 10 cities worldwide; the model shows satisfactory performance with the test data. High-latitude forests show greater seasonal dynamics of ∆Ta, generating considerable cooling of local air temperatures in warm seasons but minimal cooling or even warming effects during cool seasons, while low-latitude tropical forests always exert cooling effects with less interannual variability. The interannual dynamics of ∆Ta are significantly related to the seasonality of solar geometry and canopy leaf phenology. The differences between forest canopy temperature (Tc) and Tao, which are the two most important terms attributed by the CAS model in impacting Taf, explain a large part of forest cooling and warming (May–July: R2 = 0.35; November–January: R2 = 0.51). The novel CAS model provides a feasible way to represent the energy balance within forest ecosystems and to assess its impacts on local air temperatures globally. Keywords: Forest cooling/warming, Forest biophysical effects, Radiative transfer equation, Land-atmosphere model, Local environmental health, Climate warming mitigation

Mechanisms of cadmium (Cd)-induced inhibition of photosynthesis in the Zn/Cd hyperaccumulator Picris divaricata were investigated using photosynthesis limitation analysis. P. divaricata seedlings were grown in nutrient solution containing 0, 5, 10, 25, 50, or 75 μM Cd for 2 weeks. Total limitations to photosynthesis (TL) increased from 0% at 5 μM Cd to 68.8% at 75 μM Cd. CO2 diffusional limitation (DL) made the largest contribution to TL, accounting for 93-98% of TL in the three highest Cd treatments, compared to just 2-7% of TL attributable to biochemical limitation (BL). Microscopic imaging revealed significantly decreased stomatal density and mesophyll thickness in the three highest Cd treatments. Chlorophyll fluorescence parameters related to photosynthetic biochemistry (Fv/Fm, NPQ, ΦPSII, and qP) were not significantly decreased by increased Cd supply. Our results suggest that increased DL in leaves is the main cause of Cd-induced inhibition of photosynthesis in P. divaricata, possibly due to suppressed function of mesophyll and stomata. Analysis of chlorophyll fluorescence showed that Cd supply had little effect on photochemistry parameters, suggesting that the PSII reaction centers are not a main target of Cd inhibition of photosynthesis in P. divaricata.