China experienced worsening ground-level ozone(O_(2)) pollution from 2013 to 2019. In this study, meteorological parameters, including surface temperature(T_(2)), solar radiation(SW), and wind speed(WS), were classifi...China experienced worsening ground-level ozone(O_(2)) pollution from 2013 to 2019. In this study, meteorological parameters, including surface temperature(T_(2)), solar radiation(SW), and wind speed(WS), were classified into two aspects,(1) Photochemical Reaction Condition(PRC = T_(2)× SW) and(2) Physical Dispersion Capacity(PDC = WS). In this way, a Meteorology Synthetic Index(MSI = PRC/PDC) was developed for the quantification of meteorology-induced ground-level O_(2)pollution. The positive linear relationship between the 90 th percentile of MDA8(maximum daily 8-h average) O_(2)concentration and MSI determined that the contribution of meteorological changes to ground-level O-3 varied on a latitudinal gradient, decreasing from ~40% in southern China to 10%–20% in northern China. Favorable photochemical reaction conditions were more important for ground-level O_(2)pollution. This study proposes a universally applicable index for fast diagnosis of meteorological roles in ground-level O_(2)variability, which enables the assessment of the observed effects of precursor emissions reductions that can be used for designing future control policies.展开更多
Ground-level ozone(O_(3))is a primary air pollutant,which can greatly harm human health and ecosystems.At present,data fusion frameworks only provided ground-level O_(3)concentrations at coarse spatial(e.g.,10 km)or t...Ground-level ozone(O_(3))is a primary air pollutant,which can greatly harm human health and ecosystems.At present,data fusion frameworks only provided ground-level O_(3)concentrations at coarse spatial(e.g.,10 km)or temporal(e.g.,daily)resolutions.As photochemical pollution continues increasing over China in the last few years,a high-spatial–temporal-resolution product is required to enhance the comprehension of ground-level O_(3)formation mechanisms.To address this issue,our study creatively explores a brand-new framework for estimating hourly 2-km ground-level O_(3)concentrations across China(except Xinjiang and Tibet)using the brightness temperature at multiple thermal infrared bands.Considering the spatial heterogeneity of ground-level O_(3),a novel Self-adaptive Geospatially Local scheme based on Categorical boosting(SGLboost)is developed to train the estimation models.Validation results show that SGLboost performs well in the study area,with the R2 s/RMSEs of 0.85/19.041 lg/m^(3)and 0.72/25.112 lg/m^(3)for the space-based cross-validation(CV)(2017–2019)and historical space-based CV(2019),respectively.Meanwhile,SGLboost achieves distinctly better metrics than those of some widely used machine learning methods,such as e Xtreme Gradient boosting and Random Forest.Compared to recent related works over China,the performance of SGLboost is also more desired.Regarding the spatial distribution,the estimated results present continuous spatial patterns without a significantly partitioned boundary effect.In addition,accurate hourly and seasonal variations of ground-level O_(3)concentrations can be observed in the estimated results over the study area.It is believed that the hourly 2-km results estimated by SGLboost will help further understand the formation mechanisms of ground-level O_(3)in China.展开更多
To better understand the effects of ground-level ozone(O_(3))on nutrients and stoichiometry in different plant organs,urban tree species Celtis sinensis,Cyclocarya paliu-rus,Quercus acutissima,and Quercus nuttallii we...To better understand the effects of ground-level ozone(O_(3))on nutrients and stoichiometry in different plant organs,urban tree species Celtis sinensis,Cyclocarya paliu-rus,Quercus acutissima,and Quercus nuttallii were sub-jected to a constant exposure to charcoal-filtered air(CF),nonfiltered air(NF),or NF+40,60,or 80 nmol O_(3)mol^(-1)(NF40,NF60,and NF80)starting early in the summer of the growing season.At the end of summer,net CO_(2)assimila-tion rate(A),stomatal conductance(gs),leaf mass per area(LMA),and/or leaf greenness(SPAD)either were not sig-nificantly affected by elevated O_(3)or were even higher in some cases during the summer compared with the CF or NF controls.LMA was significantly lower in autumn only after the highest O_(3)exposures.Compared to NF,NF40 caused a large increase in gs across species in late summer and more K and Mn in stems.At the end of the growing season,nutri-ent status and stoichiometric ratios in different organs were variously altered under O_(3)stress;many changes were large and often species-specific.Across O_(3)treatments,LMA was primarily associated with C and Mg levels in leaves and Ca levels in leaves and stems.NF40 enriched K,P,Fe,and Mn in stems,relative to NF,and NF60 enhanced Ca in leaves relative to CF and NF40.Moreover,NF resulted in a higher Ca/Mg ratio in leaves of Q.acutissima only,relative to the other O_(3)regimes.Interestingly,across species,O_(3)stress led to different nutrient modifications in different organs(stems+branches vs leaves).Thus,ambient and/or elevated O_(3)exposures can alter the dynamics and distribution of nutrients and disrupt stoichiometry in different organs in a species-specific manner.Changes in stoichiometry reflect an important defense mechanism in plants under O_(3),and O_(3)pollution adds more risk to ecological stoichiometries in urban areas.展开更多
基金supported by the National Key Research and Development Plan(Grant No.2017YFC0210105)the second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0604)+7 种基金the National Natural Science Foundation of China(Grant Nos.41905086,41905107,42077205,and 41425020)the Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province(Grant No.2019B121205004)the China Postdoctoral Science Foundation(Grant No.2020M683174)the Air Quip(High-resolution Air Quality Information for Policy)Project funded by the Research Council of Norwaythe Collaborative Innovation Center of Climate ChangeJiangsu ProvinceChinathe high-performance computing platform of Jinan University。
文摘China experienced worsening ground-level ozone(O_(2)) pollution from 2013 to 2019. In this study, meteorological parameters, including surface temperature(T_(2)), solar radiation(SW), and wind speed(WS), were classified into two aspects,(1) Photochemical Reaction Condition(PRC = T_(2)× SW) and(2) Physical Dispersion Capacity(PDC = WS). In this way, a Meteorology Synthetic Index(MSI = PRC/PDC) was developed for the quantification of meteorology-induced ground-level O_(2)pollution. The positive linear relationship between the 90 th percentile of MDA8(maximum daily 8-h average) O_(2)concentration and MSI determined that the contribution of meteorological changes to ground-level O-3 varied on a latitudinal gradient, decreasing from ~40% in southern China to 10%–20% in northern China. Favorable photochemical reaction conditions were more important for ground-level O_(2)pollution. This study proposes a universally applicable index for fast diagnosis of meteorological roles in ground-level O_(2)variability, which enables the assessment of the observed effects of precursor emissions reductions that can be used for designing future control policies.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA19090104)the National Natural Science Foundation of China(No.41922008)the Hubei Provincial Natural Science Foundation of China(No.2020CFA051)。
文摘Ground-level ozone(O_(3))is a primary air pollutant,which can greatly harm human health and ecosystems.At present,data fusion frameworks only provided ground-level O_(3)concentrations at coarse spatial(e.g.,10 km)or temporal(e.g.,daily)resolutions.As photochemical pollution continues increasing over China in the last few years,a high-spatial–temporal-resolution product is required to enhance the comprehension of ground-level O_(3)formation mechanisms.To address this issue,our study creatively explores a brand-new framework for estimating hourly 2-km ground-level O_(3)concentrations across China(except Xinjiang and Tibet)using the brightness temperature at multiple thermal infrared bands.Considering the spatial heterogeneity of ground-level O_(3),a novel Self-adaptive Geospatially Local scheme based on Categorical boosting(SGLboost)is developed to train the estimation models.Validation results show that SGLboost performs well in the study area,with the R2 s/RMSEs of 0.85/19.041 lg/m^(3)and 0.72/25.112 lg/m^(3)for the space-based cross-validation(CV)(2017–2019)and historical space-based CV(2019),respectively.Meanwhile,SGLboost achieves distinctly better metrics than those of some widely used machine learning methods,such as e Xtreme Gradient boosting and Random Forest.Compared to recent related works over China,the performance of SGLboost is also more desired.Regarding the spatial distribution,the estimated results present continuous spatial patterns without a significantly partitioned boundary effect.In addition,accurate hourly and seasonal variations of ground-level O_(3)concentrations can be observed in the estimated results over the study area.It is believed that the hourly 2-km results estimated by SGLboost will help further understand the formation mechanisms of ground-level O_(3)in China.
基金supported by the National Natural Science Foundation of China(NSFC)(No.42107299).
文摘To better understand the effects of ground-level ozone(O_(3))on nutrients and stoichiometry in different plant organs,urban tree species Celtis sinensis,Cyclocarya paliu-rus,Quercus acutissima,and Quercus nuttallii were sub-jected to a constant exposure to charcoal-filtered air(CF),nonfiltered air(NF),or NF+40,60,or 80 nmol O_(3)mol^(-1)(NF40,NF60,and NF80)starting early in the summer of the growing season.At the end of summer,net CO_(2)assimila-tion rate(A),stomatal conductance(gs),leaf mass per area(LMA),and/or leaf greenness(SPAD)either were not sig-nificantly affected by elevated O_(3)or were even higher in some cases during the summer compared with the CF or NF controls.LMA was significantly lower in autumn only after the highest O_(3)exposures.Compared to NF,NF40 caused a large increase in gs across species in late summer and more K and Mn in stems.At the end of the growing season,nutri-ent status and stoichiometric ratios in different organs were variously altered under O_(3)stress;many changes were large and often species-specific.Across O_(3)treatments,LMA was primarily associated with C and Mg levels in leaves and Ca levels in leaves and stems.NF40 enriched K,P,Fe,and Mn in stems,relative to NF,and NF60 enhanced Ca in leaves relative to CF and NF40.Moreover,NF resulted in a higher Ca/Mg ratio in leaves of Q.acutissima only,relative to the other O_(3)regimes.Interestingly,across species,O_(3)stress led to different nutrient modifications in different organs(stems+branches vs leaves).Thus,ambient and/or elevated O_(3)exposures can alter the dynamics and distribution of nutrients and disrupt stoichiometry in different organs in a species-specific manner.Changes in stoichiometry reflect an important defense mechanism in plants under O_(3),and O_(3)pollution adds more risk to ecological stoichiometries in urban areas.
