• Energy Research

Although it's well known that the carbon intensity from passenger transport of cities varies widely, few studies assessed the disparities of that in city-level and its underlying factors due to the limited availability of data, and thus developed effective strategies for different types of cities. This study is the first to present a comprehensive inventory of emissions from passenger transport on road for 360 cities in mainland China for 2018, based on the data from 5 transport modes and evaluated by combining distance-based and top-down fuel-based methods. In 2018, passenger transport on road in China emitted 1076 MtC. A large portion of CO2 emissions was identified in the southern and eastern coastal areas and capital cities. GDP, population, and policy were the major factors determining the total CO2 emissions, but not carbon intensity. Clustering analysis of carbon intensity and 9 socio-economic predictors, using a tree-based regression model, clustered the 360 cities into 6 groups and showed that higher carbon intensities occurred in both affluent city groups with a high active population share and less affluent city groups with a low population density but high density of trip destinations. Forward-and-backward stepwise multiple regression analysis indicated that constructing a compact city is more effective for city groups with a high income and high active population share. Enhancing land-use mixed degree is more critical for city groups with a high income and low active population share, while shortening travel distance by intensifying infrastructure construction is more important for the less affluent city groups.

Although it's well known that the carbon intensity from passenger transport of cities varies widely, few studies assessed the disparities of that in city-level and its underlying factors due to the limited availability of data, and thus developed effective strategies for different types of cities. This study is the first to present a comprehensive inventory of emissions from passenger transport on road for 360 cities in mainland China for 2018, based on the data from 5 transport modes and evaluated by combining distance-based and top-down fuel-based methods. In 2018, passenger transport on road in China emitted 1076 MtC. A large portion of CO2 emissions was identified in the southern and eastern coastal areas and capital cities. GDP, population, and policy were the major factors determining the total CO2 emissions, but not carbon intensity. Clustering analysis of carbon intensity and 9 socio-economic predictors, using a tree-based regression model, clustered the 360 cities into 6 groups and showed that higher carbon intensities occurred in both affluent city groups with a high active population share and less affluent city groups with a low population density but high density of trip destinations. Forward-and-backward stepwise multiple regression analysis indicated that constructing a compact city is more effective for city groups with a high income and high active population share. Enhancing land-use mixed degree is more critical for city groups with a high income and low active population share, while shortening travel distance by intensifying infrastructure construction is more important for the less affluent city groups.

AbstractAlthough the biophysical effects of afforestation or deforestation on local climate are recognized, the biophysical consequences of seasonal and long-term dynamics in forests on understory microclimate, which creates microrefugia for forest organisms under global warming, remain less well understood. To fill this research gap, we combined a three-layered (i.e., canopy, forest air space and understory soil) land surface energy balance model and Intrinsic Biophysical Mechanism Model and quantify seasonal (warm minus cool seasons) and long-term changes (later minus former periods) in the biophysical effects of forest dynamics on understory air temperature (ΔTa) and soil surface temperature (ΔTs). We found that high latitudes forests show strongest negative seasonal variations in both ΔTa and ΔTs, followed by moderate latitudes forests. In contrast, low latitudes forests exhibit positive seasonal variations in ΔTa and weak negative seasonal variations in ΔTs. For the long-term variations, ΔTs increases systematically at all three latitudes. However, the situation differs greatly for ΔTs, with a weak increase at low and moderate latitudes, but a slight decrease at high latitudes. Overall, changes in sensible and latent heat fluxes induced by forest dynamics (such as leaf area index), by altering the aerodynamic resistances of canopy and soil surface layers, are the main factors driving changes in forest microclimate effects. In addition, this study also develops an aerodynamic resistance coefficient $${f}_{{\rm{r}}}^{1}$$ f r 1 to combine the air temperature effects and surface soil temperature effects and proposes an indicator – ΔTSu, that is, $$\Delta {T}_{{\rm{Su}}}=\Delta {T}_{{\rm{s}}}+(\frac{1}{{f}_{{\rm{r}}}^{1}}-1)\Delta {T}_{{\rm{a}}}$$ Δ T Su = Δ T s + ( 1 f r 1 − 1 ) Δ T a , as a possible benchmark for evaluating the total biophysical effects of forests on temperatures.

AbstractAlthough the biophysical effects of afforestation or deforestation on local climate are recognized, the biophysical consequences of seasonal and long-term dynamics in forests on understory microclimate, which creates microrefugia for forest organisms under global warming, remain less well understood. To fill this research gap, we combined a three-layered (i.e., canopy, forest air space and understory soil) land surface energy balance model and Intrinsic Biophysical Mechanism Model and quantify seasonal (warm minus cool seasons) and long-term changes (later minus former periods) in the biophysical effects of forest dynamics on understory air temperature (ΔTa) and soil surface temperature (ΔTs). We found that high latitudes forests show strongest negative seasonal variations in both ΔTa and ΔTs, followed by moderate latitudes forests. In contrast, low latitudes forests exhibit positive seasonal variations in ΔTa and weak negative seasonal variations in ΔTs. For the long-term variations, ΔTs increases systematically at all three latitudes. However, the situation differs greatly for ΔTs, with a weak increase at low and moderate latitudes, but a slight decrease at high latitudes. Overall, changes in sensible and latent heat fluxes induced by forest dynamics (such as leaf area index), by altering the aerodynamic resistances of canopy and soil surface layers, are the main factors driving changes in forest microclimate effects. In addition, this study also develops an aerodynamic resistance coefficient $${f}_{{\rm{r}}}^{1}$$ f r 1 to combine the air temperature effects and surface soil temperature effects and proposes an indicator – ΔTSu, that is, $$\Delta {T}_{{\rm{Su}}}=\Delta {T}_{{\rm{s}}}+(\frac{1}{{f}_{{\rm{r}}}^{1}}-1)\Delta {T}_{{\rm{a}}}$$ Δ T Su = Δ T s + ( 1 f r 1 − 1 ) Δ T a , as a possible benchmark for evaluating the total biophysical effects of forests on temperatures.

ABSTRACT Global change factors are known to strongly affect soil microbial community function and composition. However, as of yet, the effects of warming and increased anthropogenic nitrogen deposition on soil microbial network complexity and stability are still unclear. Here, we examined the effects of experimental warming (3°C above ambient soil temperature) and nitrogen addition (5 g N m −2 year −1 ) on the complexity and stability of the soil microbial network in a subtropical primary forest. Compared to the control, warming increased |negative cohesion|:positive cohesion by 7% and decreased network vulnerability by 5%; nitrogen addition decreased |negative cohesion|:positive cohesion by 10% and increased network vulnerability by 11%. Warming and decreased soil moisture acted as strong filtering factors that led to higher bacterial network stability. Nitrogen addition reduced bacterial network stability by inhibiting soil respiration and increasing resource availability. Neither warming nor nitrogen addition changed fungal network complexity and stability. These findings suggest that the fungal community is more tolerant than the bacterial community to climate warming and nitrogen addition. The link between bacterial network stability and microbial community functional potential was significantly impacted by nitrogen addition and warming, while the response of soil microbial network stability to climate warming and nitrogen deposition may be independent of its complexity. Our findings demonstrate that changes in microbial network structure are crucial to ecosystem management and to predict the ecological consequences of global change in the future. IMPORTANCE Soil microbes play a very important role in maintaining the function and health of forest ecosystems. Unfortunately, global change factors are profoundly affecting soil microbial structure and function. In this study, we found that climate warming promoted bacterial network stability and nitrogen deposition decreased bacterial network stability. Changes in bacterial network stability had strong effects on bacterial community functional potentials linked to metabolism, nitrogen cycling, and carbon cycling, which would change the biogeochemical cycle in primary forests.

ABSTRACT Global change factors are known to strongly affect soil microbial community function and composition. However, as of yet, the effects of warming and increased anthropogenic nitrogen deposition on soil microbial network complexity and stability are still unclear. Here, we examined the effects of experimental warming (3°C above ambient soil temperature) and nitrogen addition (5 g N m −2 year −1 ) on the complexity and stability of the soil microbial network in a subtropical primary forest. Compared to the control, warming increased |negative cohesion|:positive cohesion by 7% and decreased network vulnerability by 5%; nitrogen addition decreased |negative cohesion|:positive cohesion by 10% and increased network vulnerability by 11%. Warming and decreased soil moisture acted as strong filtering factors that led to higher bacterial network stability. Nitrogen addition reduced bacterial network stability by inhibiting soil respiration and increasing resource availability. Neither warming nor nitrogen addition changed fungal network complexity and stability. These findings suggest that the fungal community is more tolerant than the bacterial community to climate warming and nitrogen addition. The link between bacterial network stability and microbial community functional potential was significantly impacted by nitrogen addition and warming, while the response of soil microbial network stability to climate warming and nitrogen deposition may be independent of its complexity. Our findings demonstrate that changes in microbial network structure are crucial to ecosystem management and to predict the ecological consequences of global change in the future. IMPORTANCE Soil microbes play a very important role in maintaining the function and health of forest ecosystems. Unfortunately, global change factors are profoundly affecting soil microbial structure and function. In this study, we found that climate warming promoted bacterial network stability and nitrogen deposition decreased bacterial network stability. Changes in bacterial network stability had strong effects on bacterial community functional potentials linked to metabolism, nitrogen cycling, and carbon cycling, which would change the biogeochemical cycle in primary forests.