Carbon storage estimation and strategy optimization under low carbon objectives for urban attached green spaces.

In the context of rapid urbanization, scarce land resources have highlighted the importance of attached green spaces (AGS), which have received limited attention despite their critical importance in the urban carbon cycle. Analyzing the differences in carbon storage of different AGS types and proposing different optimization strategies can provide a reference for urban managers to scientifically enhance the carbon sinks of greenfield. This study estimated the carbon storage of AGS in central Shanghai using a series of detailed field survey data and remote sensing data. The results showed that AGS stored 296 Gg (1Gg = 109 g) of carbon, accounting for 56 % of the total carbon storage in all urban green spaces. While carbon density in AGS is lower than that in other green space types due to the dominance of small trees, simple vegetation structures and poor maintenance in some areas. Significant differences in carbon storage capacity were also found among different types of AGS, related to individual vegetation attributes and vegetation structure. Our findings emphasized that optimal design strategies should be different for various green space types, and proposed corresponding optimization strategies for different AGS types. Furthermore, the dual role of multi-layered planting structures in carbon sinks and biodiversity was also emphasized.

Explore the spatial pattern of carbon emissions in urban functional zones: a case study of Pudong, Shanghai, China.

It is crucial for the development of carbon reduction strategies to accurately examine the spatial distribution of carbon emissions. Limited by data availability and lack of industry segmentation, previous studies attempting to model spatial carbon emissions still suffer from significant uncertainty. Taking Pudong New Area as an example, with the help of multi-source data, this paper proposed a research framework for the amount calculation and spatial distribution simulation of its CO2 emissions at the scale of urban functional zones (UFZs). The methods used in this study were based on mapping relations among the locations of geographic entities and data of multiple sources, using the coefficient method recommended by the Intergovernmental Panel on Climate Change (IPCC) to calculate emissions. The results showed that the emission intensity of industrial zones and transport zones was much higher than that of other UFZs. In addition, Moran's I test indicated that there was a positive spatial autocorrelation in high emission zones, especially located in industrial zones. The spatial analysis of CO2 emissions at the UFZ scale deepened the consideration of spatial heterogeneity, which could contribute to the management of low carbon city and the optimal implementation of energy allocation.

Identify the effects of urbanization on carbon emissions (EUCE): a global scientometric visualization analysis from 1992 to 2018.

The effects of urbanization on carbon emissions (EUCE) are complex, while rare work has comprehensively elaborated on how various aspects affect and develop. In this study, utilizing Citespace and VOSviewer software, a global scientometric visualization analysis was conducted to excavate various impacts and future trends of urbanization on carbon emissions. Based on publications from the year 1982 to 2018, the spatial-temporal distribution of publications, collaboration, current hotspots, and future trends of EUCE were carried out. The results indicated that between 1992 and 2018, there were accelerated increasing trends of EUCE researches world widely, among which China, the USA, and UK ranked the top 3. Relevant research firstly appeared in the USA, while grew most rapidly in China. Research subjects mainly concentrate on population migration, resource consumption, land use and land cover change (LULCC), energy conservation, non-carbon greenhouse gases like CH4 and N2O. And attention on carbon footprint has become a hotspot for carbon mitigation. For research fronts, ecosystem service offered by urban green space has gradually evolved as a research focus. Besides, energy transformation technology is critical for mitigating carbon emissions and has become an important concern in the future development. Furthermore, the timeline visualization analysis indicates that all the research topics related to EUCE are cited and connected with each other, reflecting the necessity of interdisciplinary integration in scientific research. Overall, our study has provided a quantitative visualization on the current situation and future trends of EUCE subject, which will be helpful to subsequent research and policy guidance.

Prediction of future carbon footprint and ecosystem service value of carbon sequestration response to nitrogen fertilizer rates in rice production.

There is concern for variations of the carbon footprint (CF) and ecosystem service value of carbon sequestration (ESVCS) related to nitrogen (N) fertilizer rate in rice production under future climate change. To explore possible future ecological effects of N fertilizer rate, a DeNitrification-DeComposition (DNDC) model combined with Representative Concentration Pathway (RCP) projections (RCP 4.5 and RCP 8.5) were used to predict the CF and ESVCS of rice production. The model was validated by a two-year field experiment, and then seven N fertilizer levels (0, 75, 150, 190, 225, 300, and 375 kg N/ha) were set for prediction from 2015 to 2050. The validation results indicated a good fit between the DNDC-simulated and observed data of GHG emission and rice yield. Under RCP 8.5, the mean CF was 4.5-8.7% higher and the average ESVCS was 3.6-7.4% lower than those under RCP 4.5. The effects of N fertilizer rate on CF and ESVCS were consistent between the two climate change scenarios. In both RCPs, it was found that CF and ESVCS were mainly influenced by N fertilizer rate due to the latter's effect on CH4 emissions and crop carbon fixation. CH4 was the main contributor to CF during 2015-2050, accounting for 43.9-58.3% of the total CF. Agricultural inputs were also large contributors to CF, and N fertilizer increased the indirect GHG emissions by 24.6-122.2% compared with no N fertilization treatment. Among the studied N fertilizer rates, 190 kg N/ha was the optimal rate, obtaining the lowest CF and highest ESVCS. These results indicate that, under future climate change, an N fertilizer rate of 190 kg N/ha could achieve a trade-off between high yield, reduction of CF, and improvement of ESVCS in rice production.

Evaluation of satellite rainfall products for modeling water yield over the source region of Blue Nile Basin.

Rainfall data is a vital input for many ecosystem service modeling in general and hydrological modeling in particular. However, accurate rainfall data with sufficient spatiotemporal distribution is inadequate in the Blue Nile Basin (Ribb watershed) due to uneven distribution of rain gauge networks. Advances in remote sensing science have provided alternative sources of rainfall data with high spatiotemporal resolution. But the accuracies of different satellite rainfall datasets are not uniform across space and time that need to be checked. The overarching objective of this study is to evaluate the performance of four satellite-based rainfall products [Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT-v2.0 and v3.0), Climate Hazards Group InfraRed Precipitation with Station data version two (CHIRPS-v2.0), and Tropical Rainfall Measuring Mission version seven (TRMM-3B43 v7.0)] in the data-scarce region of the Blue Nile Basin in Ethiopia. The evaluation was carried out through direct comparison with the observed rainfall and through simulation of annual water yield using InVEST model for monthly, seasonal, and annual time scales. In general, the results show that the performance of satellite rainfall differs in time scale, topography, and method of evaluation. CHIRPS v2.0 rainfall product shows good performance both at monthly (R2 = 0.83) and annual (r = 0.85) time scales regardless of elevation. TRMM-3B43 v7.0 well performed over the mountainous area, which makes it the best rainfall data than other products at seasonal time scale (r = 0.86). CHIRPS v2.0 and TAMSAT v3.0 are equally applicable to that of gauged rainfall data for annual water yield simulation (Bias = 1.01 and 1.08 respectively). The findings of this study indicated the best performance of CHIRPS v2.0 and TAMSAT v3.0 satellite rainfall products, and hence, these products can be used for water management and decision-making process, particularly in the data-scarce watersheds.

Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China.

Land-use and land-cover change (LUCC) is a crucial factor affecting carbon emissions. Zhejiang Province has witnessed unprecedented LUCC concomitant with rapid urbanization from 1970 to 2010. In this study, remote sensing, geographic information system (GIS) and the Intergovernmental Panel on Climate Change (IPCC) method were combined to quantify changes in both vegetation carbon storage and soil organic carbon (SOC) storage resulting from LUCC during 1970-1990 and 1990-2010. For both 1970-1990 and 1990-2010, the results showed successive decrease in farmlands (2.8 × 105 ha or -9.15% and 5.9 × 105 ha or -20.49%, respectively) and grasslands (3.4 × 104 ha or -10.73% and 1.5 × 105 ha or -54.1%, respectively), and continuous increase in forests (2.0 × 104 ha or 0.33% and 1.7 × 105 ha or 2.81%, respectively) and built-up lands (2.07 × 105 ha or 78.41% and 6.49 × 105 ha or 137.8%, respectively). From 1970 to 1990, approximately 8.3 Tg of the total carbon sink declined, including a 0.4 Tg reduction in vegetation carbon and a 7.9 Tg reduction in SOC. While from 1990 to 2010, approximately 17.5 Tg of carbon storage declined, comprising a 2.8 Tg of carbon accumulated by vegetation, and a 20.3 Tg reduction in SOC. Overall, LUCC has resulted in huge amount of carbon emissions in Zhejiang from 1970 to 2010. Efficient planning for LUCC and gradual mitigation of carbon emissions are indispensable for future urban development in China under increasing pressure from global warming.