Soil CO 2 efflux is a major pathway of carbon loss from terrestrial ecosystems to the atmosphere, and its response to biochar application may vary with soil, climate, and management conditions. This study evaluated whether biochar increases soil carbon concentration and rubber tree biomass without stimulating soil CO 2 efflux in a strongly acidic tropical plantation soil in northeastern Thailand. A two-year field experiment compared four management treatments: T1 (control; 200 g tree −1 of 20:10:12 fertilizer), T2 (2 t ha −1 biochar + 200 g tree −1 fertilizer), T3 (2 t ha −1 biochar + 500 g tree −1 fertilizer), and T4 (4 t ha −1 biochar + 200 g tree −1 fertilizer). Soil pH, soil organic carbon (SOC), rubber tree growth and biomass carbon, and monthly soil CO 2 efflux were monitored for 2 years. Biochar increased soil pH, and SOC relative to the control. In the second year, T2 and T3 also increased rubber tree height, stem diameter, biomass and biomass carbon. Mean soil CO 2 efflux was 577.24 ± 281.65, 530.55 ± 223.59, 468.63 ± 138.19 and 560.48 ± 270.17 mg CO 2 m −2 day −1 in T1–T4, respectively, with no significant treatment effect. Second-year cumulative soil CO 2 efflux ranged from 146.41 to 176.25 g CO 2 m −2 year −1 and did not differ significantly among treatments. Efflux was higher in the wet season than in the dry season, whereas monthly relationships with soil temperature and moisture were weak and non-significant. The results indicate that biochar increased measured SOC concentration and was associated with greater estimated rubber tree biomass carbon under certain treatments, without a consistent increase in soil CO 2 efflux. However, changes in soil carbon stocks and long-term sequestration could not be established from the available measurements.
Air-conditioning operation imposes an additional auxiliary load on heavy-duty diesel vehicles, yet its effects on conventional pollutant emissions, particularly under high ambient temperatures, remain insufficiently understood. In this study, six heavy-duty diesel vehicles, including dump trucks, freight trucks, a coach, and a tractor-trailer, were tested over vehicle-specific China Heavy-duty Commercial Vehicle Test Cycles in a climate-controlled chassis dynamometer laboratory. Experiments were conducted at ambient temperatures of 32 and 42 °C with air conditioning switched off and on. Carbon monoxide (CO), nitrogen oxides (NOx), and particle number (PN) emissions were evaluated using whole-cycle distance- and work-based emission factors, stage-resolved analysis, transient emission profiles, a high-temperature modulation index, and exploratory machine-learning analysis. At 32 °C, air-conditioning operation produced pollutant and vehicle-specific responses. Whole-cycle CO emissions changed only moderately, whereas NOx responses varied in both direction and magnitude among vehicles. PN exhibited the most consistent positive response, with higher distance-based emission factors observed for all six vehicles during air-conditioning operation. Stage-resolved analysis showed that these effects were not uniformly distributed throughout the driving cycles: CO responses were concentrated mainly in low-speed or urban stages, while NOx and PN responses depended on specific vehicle–stage combinations. Increasing the ambient temperature from 32 to 42 °C increased the AC-induced relative changes in distance-based NOx for Vehicle E and PN for Vehicle F by 123.7 and 82.7 percentage points, respectively, while the CO interaction indices were mostly negative. Exploratory machine-learning results further indicated scenario-dependent changes in the variables associated with second-by-second emission variability. Overall, the results show that air-conditioning-related emissions from heavy-duty diesel vehicles vary by pollutant, vehicle, driving stage, and ambient temperature, highlighting the need to consider auxiliary cooling loads when evaluating emissions under warm and high-temperature operating conditions.
Soil CO2 efflux is a major pathway of carbon loss from terrestrial ecosystems to the atmosphere, and its response to biochar application may vary with soil, climate, and management conditions. This study evaluated whether biochar increases soil carbon concentration and rubber tree biomass without stimulating soil CO2 efflux in a strongly acidic tropical plantation soil in northeastern Thailand. A two-year field experiment compared four management treatments: T1 (control; 200 g tree−1 of 20:10:12 fertilizer), T2 (2 t ha−1 biochar + 200 g tree−1 fertilizer), T3 (2 t ha−1 biochar + 500 g tree−1 fertilizer), and T4 (4 t ha−1 biochar + 200 g tree−1 fertilizer). Soil pH, soil organic carbon (SOC), rubber tree growth and biomass carbon, and monthly soil CO2 efflux were monitored for 2 years. Biochar increased soil pH, and SOC relative to the control. In the second year, T2 and T3 also increased rubber tree height, stem diameter, biomass and biomass carbon. Mean soil CO2 efflux was 577.24 ± 281.65, 530.55 ± 223.59, 468.63 ± 138.19 and 560.48 ± 270.17 mg CO2 m−2 day−1 in T1–T4, respectively, with no significant treatment effect. Second-year cumulative soil CO2 efflux ranged from 146.41 to 176.25 g CO2 m−2 year−1 and did not differ significantly among treatments. Efflux was higher in the wet season than in the dry season, whereas monthly relationships with soil temperature and moisture were weak and non-significant. The results indicate that biochar increased measured SOC concentration and was associated with greater estimated rubber tree biomass carbon under certain treatments, without a consistent increase in soil CO2 efflux. However, changes in soil carbon stocks and long-term sequestration could not be established from the available measurements.
Aircraft-induced condensation trails (contrails) cause a significant portion of aviation’s climate impact. Thus, predicting airspaces susceptible to the formation of strongly warming contrails is crucial for operational mitigation strategies. Forecasting such regions is affected by the uncertainty of the meteorological conditions and relies on assumptions of the aircraft’s technical parameters and direction of flight, the latter being relevant due to wind shear acting normal to the contrail’s axis. This study aims at quantifying these uncertainties using the Contrail Cirrus Prediction Tool (CoCiP). Ensemble simulations were conducted for 12 weeks in 2019 over Europe and the North Atlantic, varying meteorology (10 members), aircraft type (10 types), and heading (7 directions) to assess the variabilities these inputs introduce in the prediction of high impact regions as well as their diurnal and seasonal dependence. We define variability as the ratio of the standard deviation to the mean across the model outputs of each ensemble. As meteorology ensemble, the Ensemble of Data Assimilations, which is provided by the European Centre for medium range weather forecasts, has been used. The aircraft types have been selected to represent the air traffic in terms of emissions and aircraft mass, spanning from 55t to 425t. The results indicate that aircraft characteristics and meteorology are the dominant and similarly important sources of variability in predicted high impact regions (mean variabilities of 0.43 and 0.41), whereas aircraft heading has a substantially smaller influence (0.13). Aircraft characteristics produce the largest variability in total high impact volume, while meteorological uncertainty particularly affects the spatial distribution, with 30% of grid points considered as high impact by only one single meteorological ensemble member. This highlights the importance of considering uncertainties in both meteorological forecasts and aircraft performance and emissions when identifying high-impact regions and optimizing contrail avoidance trajectories. Climate impact in high-impact regions is 25% larger in winter than in summer, while the associated variability increases by only up to 12%. At night, climate impact is up to 33% larger than during daytime, with variability due to aircraft characteristics and meteorology decreasing by up to 56%. Coverage of high impact regions in winter and at night is up to a factor of 3 higher than during the day and summer. These findings suggest that contrail mitigation may be particularly effective during nighttime and winter conditions, when predicted climate benefits are larger and variability is lower.
