The local climate zone (LCZ) classification scheme provides a standardized method to characterize urban morphological characteristics and urban thermal environments. However, its capability to differentiate urban temperatures has not been well examined. This study investigated the LCZ-based land surface temperature (LST) in five megacities, including Shenyang, Beijing, Xi'an, Nanjing, and Nanchang. The results indicate that the LCZ scheme might conceal areas with the most critical heat risks, if the maximum LST was not used. The built-dominated zones often contributed to urban temperature increase, but it was not always true. The non-built-dominated zones, mostly lowered urban temperatures, while they could contribute to urban temperature increase depending on seasonal and urban context. Both hot and cold non-built-dominated zones varied significantly with city and season. Some zones were the hottest in one season, but changed to be the coldest in another season. LCZ scheme showed good capability to differentiate the temperatures of built-dominated zones, while its capability to characterize non-built-dominated zones was weaker. In Beijing, the LCZ capability to characterize the temperature of non-built-dominated zones was below 70%, and was only 16.67% in summer. Therefore, urban planners, designers, and managers should prudently adopt LCZ scheme to rank the priorities for integrating cooling interventions in both built-dominated and non-built-dominated zones. It is important to not copy the LCZ–based LST pattern of other cities or seasons when making decisions. Overall, this study provides a reference to understand LCZ capability and make proper decisions for urban heat mitigation, adaptation, and management.

Methane (CH₄) is one of the three most important greenhouse gases. To date, observations of ecosystem-scale methane (CH₄) fluxes in forests are currently lacking in the global CH₄ budget. The environmental factors controlling CH₄ flux dynamics remain poorly understood at the ecosystem scale. In this study, we used a state-of-the-art eddy covariance technique to continuously measure the CH₄ flux from 2016 to 2018 in a subtropical forest of Zhejiang Province in China, quantify the annual CH₄ budget and investigate its control factors. We found that the total annual CH₄ budget was 1.15 ± 0.28~4.79 ± 0.49 g CH₄ m⁻² year⁻¹ for 2017–2018. The daily CH₄ flux reached an emission peak of 0.145 g m⁻² d⁻¹ during winter and an uptake peak of −0.142 g m⁻² d⁻¹ in summer. During the whole study period, the studied forest region acted as a CH₄ source (78.65%) during winter and a sink (21.35%) in summer. Soil temperature had a negative relationship (p < 0.01; R² = 0.344) with CH₄ flux but had a positive relationship with soil moisture (p < 0.01; R² = 0.348). Our results showed that soil temperature and moisture were the most important factors controlling the ecosystem-scale CH₄ flux dynamics of subtropical forests in the Tianmu Mountain Nature Reserve in Zhejiang Province, China. Subtropical forest ecosystems in China acted as a net source of methane emissions from 2016 to 2018, providing positive feedback to global climate warming.

Tropical rainforest ecosystems are important when considering the global methane (CH₄) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH₄ fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH₄ flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH₄ uptake generally occurred in this tropical rainforest, where strong CH₄ uptake occurred in the daytime, and a weak CH₄ uptake occurred at night with a mean daily CH₄ flux of −4.5 nmol m⁻² s⁻¹. In this rainforest, the mean annual budget of CH₄ for the 3 years was −1260 mg CH₄ m⁻² year⁻¹. Furthermore, the daily averaged CH₄ flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH₄ flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (T_air), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (T_soil), although the linear correlation between the daily CH₄ flux and any of these individual variables was relatively low. This indicates that CH₄ uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH₄ sink during 2016–2018, helping to counteract global warming.

Although rice paddy fields are one of the world’s largest anthropogenic sources of methane CH₄, the budget of ecosystem CH₄ and its’ controls in rice paddies remain unclear. Here, we analyze seasonal dynamics of direct ecosystem-scale measurements of CH₄ flux in a rice-wheat rotation agroecosystem over 3 consecutive years. Results showed that the averaged CO₂ uptakes and CH₄ emissions in rice seasons were 2.2 and 20.9 folds of the wheat seasons, respectively. In sum, the wheat-rice rotation agroecosystem acted as a large net C sink (averaged 460.79 g C m⁻²) and a GHG (averaged 174.38 g CO₂eq m⁻²) source except for a GHG sink in one year (2016) with a very high rice seeding density. While the linear correlation between daily CH₄ fluxes and gross ecosystem productivity (GEP) was not significant for the whole rice season, daily CH₄ fluxes were significantly correlated to daily GEP both before (R²: 0.52–0.83) and after the mid-season drainage (R²: 0.71–0.79). Furthermore, the F partial test showed that GEP was much greater than that of any other variable including soil temperature for the rice season in each year. Meanwhile, the parameters of the best-fit functions between daily CH₄ fluxes and GEP shifted between rice growth stages. This study highlights that GEP is a good predictor of daily CH₄ fluxes in rice paddies.