China implemented continuous forestation and experienced significant greening tendency in the past several decades. While the ecological project brings benefits to regional carbon assimilation, it also affects surface ozone (O3) pollution level through perturbations in biogenic emissions and dry deposition. Here, we use a coupled chemistry-vegetation model to assess the impacts of land use and land cover change (LULCC) on summertime surface O3 in China during 2000-2019. The LULCC is found to enhance O3 by 1-2 ppbv in already-polluted areas. In contrast, moderate reductions of -0.4 to -0.8 ppbv are predicted in southern China where the largest forest cover changes locate. Such inconsistency is attributed to the background chemical regimes with positive O3 changes over VOC-limited regions but negative changes in NOx-limited regions. The net contribution of LULCC to O3 budget in China is 24.17 Kg/s, in which the positive contribution by more isoprene emissions almost triples the negative effects by the increased dry deposition. Although the LULCC-induced O3 perturbation is much lower than the effects of anthropogenic emissions, forest expansion has exacerbated regional O3 pollution in North China Plain and is expected to further enhance surface O3 with continuous forestation in the future.

The terrestrial ecosystem in China mitigates 21%-45% of the national contemporary fossil fuel CO2 emissions every year. Maintaining and strengthening the land carbon sink is essential for reaching China\'s target of carbon neutrality. However, this sink is subject to large uncertainties due to the joint impacts of climate change, air pollution, and human activities. Here, we explore the potential of strengthening land carbon sink in China through anthropogenic interventions, including forestation, ozone reduction, and litter removal, taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate models. Without anthropogenic interventions, considering Shared Socioeconomic Pathways (SSP) scenarios, the land sink is projected to be 0.26-0.56 Pg C a-1 at 2060, to which climate change contributes 0.06-0.13 Pg C a-1 and CO2 fertilization contributes 0.08-0.44 Pg C a-1 with the stronger effects for higher emission scenarios. With anthropogenic interventions, under a close-to-neutral emission scenario (SSP1-2.6), the land sink becomes 0.47-0.57 Pg C a-1 at 2060, including the contributions of 0.12 Pg C a-1 by conservative forestation, 0.07 Pg C a-1 by ozone pollution control, and 0.06-0.16 Pg C a-1 by 20% litter removal over planted forest. This sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060, providing a solid foundation for the carbon neutrality in China.

ICTs and access to Internet use are considered vital for the achievement of sustainable development goals. So, this study explored the effect of the global digital divide, trade openness, renewable energy consumption, and forestation on greenhouse gas (GHG) emissions in 42 high-income countries (HICs) and high-middle-income (HMICs), low-income countries (LICs), and low-middle-income countries (LMICs) of Africa from 1990 to 2018. TheDumitrescu-Hurlin causality results confirmed a unidirectional causality from GHG emissions to the global digital divide (HICs and HMICs), global digital divide to GHG emissions (LICs), and GHG emission to trade openness (LICs and LMICs). Moreover, the long-run results of the autoregressive distributed lag (ARDL) model showed an increase in GHG due to an increase in the global digital divide in all three panels. Further, ARDL results showed reduced GHG emissions due to increased trade openness in LIC and LMICs, renewable energy consumption, and forestation in all three panels. Thus, to encounter pollution from Internet use, the government should start environment-friendly projects through public and private investment in smart and modern environment-friendly technology and reduce the taxes and tariffs on them. Moreover, the governments of African countries should create public awareness through print and electronic media for raising the forestation area.

Forestation is important for sequestering atmospheric carbon, and it is a cost-effective and nature-based solution (NBS) for mitigating global climate change. Here, under the assumption of forestation in the potential plantable lands, we used the forest carbon sequestration (FCS) model and field survey involving 3365 forest plots to assess the carbon sequestration rate (CSR) of Chinese existing and new forestation forests from 2010 to 2060 under three forestation and three climate scenarios. Without considering the influence of extreme events and human disturbance, the estimated average CSR in Chinese forests was 0.358 ± 0.016 Pg C a-1, with partitioning to biomass (0.211 ± 0.016 Pg C a-1) and soil (0.147 ± 0.005 Pg C a-1), respectively. The existing forests account for approximately 93.5% of the CSR, which will peak near 2035, and decreasing trend was present overall after 2035. After 2035, effective tending management is required to maintain the high CSR level, such as selective cutting, thinning, and approximate disturbance. However, new forestation from 2015 in the potential plantable lands would play a minimal role in additional CSR increases. In China, the CSR is generally higher in the Northeast, Southwest, and Central-South, and lower in the Northwest. Considering the potential losses through deforestation and logging, it is realistically estimated that CSR in Chinese forests would remain in the range of 0.161-0.358 Pg C a-1 from 2010 to 2060. Overall, forests have the potential to offset 14.1% of the national anthropogenic carbon emissions in China over the period of 2010-2060, significantly contributing to the carbon neutrality target of 2060 with the implementation of effective management strategies for existing forests and expansion of forestation.

In this study, a comparative literature-based assessment of the impact of operational factors such as climatic condition, vegetation type, availability of land, water, energy and biomass, management practices, cost and soil characteristics was carried out on six greenhouse gas removal (GGR) methods. These methods which include forestation, enhanced weathering (EW), soil carbon sequestration (SCS), biochar, direct air capture with carbon storage (DACCS) and bioenergy with carbon capture and storage (BECCS) were accessed with the aim of identifying the conditions and requirements necessary for their optimum performance. The extent of influence of these factors on the performance of the various GGR methods was discussed and quantified on a scale of 0-5. The key conditions necessary for optimum performance were identified with forestation, EW, SCS and biochar found to be best deployed within the tropical and temperate climatic zones. The CCS technologies (BECCS and DACCS) which have been largely projected as major contributors to the attainment of the emission mitigation targets were found to have a larger locational flexibility. However, the need for cost optimal siting of the CCS plant is necessary and dependent on the presence of appropriate storage facilities, preferably geological. The need for global and regional cooperation as well as some current efforts at accelerating the development and deployment of these GGR methods were also highlighted.

Evapotranspiration (ET) is a central process in the climate system that plays a crucial role in the regional water cycle and climate regulation. However, estimating the effects of regional ET on the regional water cycle and climate regulation remains challenging due to the lack of quantitative methods and large-scale direct observational data. This study develops a new method to estimate evapotranspiration at regional scales using long-term monitoring data and the bootstrap resampling approach to calculate the ET unit area per year for China. This study applies the deviance information criterion as a goodness-of-fit index to select the most optimal formula for estimating regional ET for different climatic zones in China. The bootstrap resampling method was used to estimate parameter distribution in different climatic zones based on the outcome of 2000 trials. The results show that the predicted ET of adjacent climates overlaps with each other. The subtropical monsoonal climatic zone had the widest range of predicted ET (0-8000 mm/year), followed by the temperate and monsoonal climatic zones (0-1500 mm/year), mountain plateau climatic zone (0-1000 mm/year), and temperate continental climatic zone (0-500 mm/year). The probability distributions and isopleths of regionally predicted ET were also determined for China. The methods used in this study provide a promising tool to assess the effects of introducing large-scale forestation or restoration of trees on local water resources management.

In 1996, a diagnostic study performed in a 16-ha field located in Buenos Aires Province (Argentina), where a chemical industry produced 1,2,3,4,5,6-hexachlorocyclohexane (HCH) from 1960 to 1978, showed contamination with HCH ranging from 10 to 20,000 mg kg-1 dry soil (706.4 mg kg-1 average). For remediation purposes, a forestation plan was put into practice in 1997 employing approximately 12,300 Eucalyptus dunnii seedlings which by 2016 where fully grown into trees that formed a forest where local fauna can be found. Midterm analysis done in 2005, when E. dunnii trees had developed into 8-10 m high trees, indicated that HCH was incorporated into leaves and logs and soil phytoremediation was progressing. Final quantitation analysis of HCH in soil performed in 2016 demonstrated that the 97.2% of the field area was effectively decontaminated with 98.1% overall average efficiency. Thus, this work is the first global example of a successful employment of E. dunnii trees for HCH phytoremediation purposes at field scale. These results may encourage other researchers to test the ability of E. dunnii to phytoremediate soils contaminated with other chlorinated compounds like polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs).

Forest regeneration and expansion are occurring in many countries, with 80 million ha established from 2000 to 2012 under the Bonn accord and 17.5 million ha established from 1990 to 2005 according to the Food and Agriculture Organisation. Multiple reviews have linked increasing forest cover with reduced river flow and potentially detrimental effects downstream. Previous reviews have investigated trends in river flow response over time, but the influence of forest age remains uncertain. Partial river flow recovery (towards non-forested conditions) has been reported in decades following forest establishment, but the role of climate in driving these trends has not been explored. Here, we evaluate river flow trends in 43 studies following forest establishment, which provide sufficient information to distinguish the effects of ageing forests from variable climate. Our meta-analysis supports previous findings showing that forestation reduces annual river flow (by 23% after 5 years and 38% after 25 years) with greater reductions in catchments with higher mean annual precipitation, larger increases in forest cover, and which were idle, rather than agricultural land, prior to forestation. The impact of forests on river flow is sensitive to annual precipitation and potential evapotranspiration, but responses are highly variable. Forests affect river flow less when annual precipitation is low, and sensitivity to precipitation decreases as catchment aridity increases. The majority of catchments demonstrated persistent river flow declines after forest establishment. However, nine catchments showed partial flow recovery after an initial decrease, with peak flow reductions at an average age of 15 and across a range of tree species. The mean rate of recovery was 34 mm/year over 5 years. Partial flow recovery with forest age cannot be commonly expected, however, and forestation programmes should take into account that changes to annual river flow are likely to persist for up to five decades.

Random forests (RF) is a powerful species distribution model (SDM) algorithm. This ensemble model by default can produce categorical and numerical species distribution maps based on its classification tree (CT) and regression tree (RT) algorithms, respectively. The CT algorithm can also produce numerical predictions (class probability). Here, we present a detailed procedure involving the use of the CT and RT algorithms using the RF method with presence-only data to model the distribution of species. CT and RT are used to generate numerical prediction maps, and then numerical predictions are converted to binary predictions through objective threshold-setting methods. We also applied simple methods to deal with collinearity of predictor variables and spatial autocorrelation of species occurrence data. A geographically stratified sampling method was employed for generating pseudo-absences. The detailed procedural framework is meant to be a generic method to be applied to virtually any SDM prediction question using presence-only data. •How to use RF as a standard method for generic species distributions with presence-only data•How to choose RF (CT or RT) methods for the distribution modeling of species•A general and detailed procedure for any SDM prediction question.

Species selection is a crucial step in the planning phase of forestation programs given its impact on the results and on stakeholder interactions. This study develops a planning tool for forestation programs that incorporates the selection of tree species and the scheduling of planting and harvesting, while balancing the maximization of the carbon sequestered and income realized, into the forestation decision-making and planning process. The validation of the goal programming model formulated demonstrates that the characteristics of natural tree species along with the behavior of growth and timing of yield are significant factors in achieving the environmental and socio-economic aspirations. The proposed model is therefore useful in gauging species behavior and performance over time. Sensitivity analysis was also conducted where the behavior of the income generated and carbon sequestered with respect to the external factors such as carbon market prices, percentage area allocated for protection and discount factor was assessed.