Coastal urbanization alters carbon cycling in Tokyo Bay

The carbon emissions related to the land-use changes from 2000 to 2015 in Shenzhen, China: Implication for exploring low-carbon development in megacities

Megacities exploit enormous amounts of lands from outside of the city boundary. However, there is a large knowledge gap in the impact of socioeconomic activities associated land-use changes on carbon emissions of megacities during the urbanization. In the current work, we combined the material-flow analysis, environmental extended input-output model, and land matrix data to construct a hybrid network framework. Such a framework was used to estimate the carbon emissions driving from trade between sectors and associated land use changes during 2000-2015 in Shenzhen, China. Results indicated that the total carbon emissions of Shenzhen had a growth rate of 262.7% from 2000 to 2010 and a declining rate of 17.6% from 2010 to 2015. This pattern is associated with large declining rates in the overall energy and carbon intensities by 53.8% and 63.2% during the period of 2000-2015. Meanwhile, embodied carbon emissions of Shenzhen kept rising by approximately twofold, accompanied by the increasing trends in the land-use related carbon emissions both inside and outside of city boundary. The land uses per unit GDP showed a dramatical decline by 85.7% and with a large contribution of the transportation and industrial land, and this caused a gradual increase in overall land-use related emissions with average growth rate of 7.1%. In addition, the land-use change related carbon emissions of the transportation and industrial land had a cumulative growth of 85%. As for the embodied land-use related carbon emissions, the dominated contributor was the Agriculture sector which drove an average of 0.13 MtC yr^-1 emissions via importing agricultural products from outside of Shenzhen. This study provides a scientific foundation for corporately mitigate carbon emissions between megacities and their surrounding regions.

Assessing spatiotemporal sources of biogenic and anthropogenic sedimentary organic matter from the mainstream Haihe River, China: Using n-alkanes as indicators

Sedimentary organic matter (SOM) plays an important role in the transportation and transformation of various pollutants and the carbon cycle in aquatic and terrestrial ecosystems, especially for seagoing rivers. However, few studies have focused on the sources and factors of SOM in rivers under the significant pressure of high urbanization and industrialization. In this study, we adopted the molecular markers of n-alkanes and their proxies in the mainstream Haihe River to reveal the spatiotemporal distributions and biogenic and anthropogenic sources of SOM. The concentrations of Σ₂₉n-alkanes, Σ_biogenicn-alkanes, and Σ_{anthropogenic}n-alkanes were 4985.6 (127.5-26,296.6), 1872.1 (38.1-9216.9), and 3113.5 (89.4-18,259.7) ng·g^-1 dw (dry weight), respectively. Hybrid sources of n-alkanes were found in this study. The composition distribution and proxies of n-alkanes showed that woody and herbaceous plants are the main sources of biogenic SOM, while incomplete fossil fuel burning and heavy oil emissions served as the main contributors to anthropogenic SOM in the mainstream Haihe River, especially through industrial activities. The average chain length of biogenic n-alkanes (ACL_bio) was verified to quantify the relative contributions of biogenic sources of SOM and proxies; the average chain length of anthropogenic n-alkanes (ACL_anthro), and the ratio of unit short‑carbon to unit long‑carbon anthropogenic n-alkanes (L/H) were verified to quantify the relative contributions of anthropogenic sources of SOM in the river system. Impacts from sedimentary geochemistry (such as total organic carbon (TOC) and grain size of sediments) on n-alkanes were explored, and the correlations of Σ₂₉n-alkanes with TOC and grain size of the river sediment indicated that terrestrial organic matter was the main source of SOM, while emissions from incomplete combustion and intensive manufacturer activities should also not be neglected.

Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China

Improving our understanding of the patterns and drivers of regional carbon budgets is critical to mitigating climate change regionally and globally. Different from previous research, our study attempts to reveal the comprehensive impact of climate change and human activities factors on the carbon budget. Based on the Carnegie–Ames–Stanford approach (CASA) model, the IPCC inventory method, the ordinary least squares (OLS) regression model, the Geodetector model, and the geographically weighted regression (GWR) method, we investigated the spatiotemporal patterns of the carbon budget in the Yangtze River Delta (YRD) region from 2000 to 2015 and analyzed the effects of climate change and human activities on the carbon budget. The results showed that the carbon budget in the YRD region changed from 271.33 million tons in 2000 to −1193.76 million tons in 2015. During this period, the changes in the carbon budget per unit area in the four provinces all showed a decreasing trend, among which Shanghai decreased the most, followed by Jiangsu, Zhejiang and Anhui. In terms of spatial pattern, the carbon budget of the YRD region has a “core-edge” structural feature. The closer it is to Shanghai, the core area, the more severe the carbon budget deficit; the farther from it, the greater the carbon budget surplus. Overall, we found that human activities have a greater impact on the carbon budget than climate change. The top three drivers were, in order, changes in population density, GDP per capita, and unused land, with q values of 0.3317, 0.1202, and 0.0998, respectively. Locally, the impact of the drivers on the carbon budget shows obvious spatial heterogeneity. In particular, the population density was negatively correlated with carbon budget changes in the entire study area, and the coefficients of GDP per capita and unused land were negative in most counties. Based on the results, we put forward suggestions for restricting population flow among the core area and the peripheral area, promoting industrial innovation in the core area and ecological protection in the peripheral area, as well as implementing three-dimensional space development in the core area and controlling the expansion of construction land in the peripheral area. Our study can provide a scientific basis for low-carbon development in the YRD region. The methodology and findings of this study can provide references for similar studies in other urbanized regions around the world.

Remote sensing of seawater optical properties and the subsurface phytoplankton layer in coastal waters using an airborne multiwavelength polarimetric ocean lidar

The vertical profiles of the seawater optical properties and subsurface phytoplankton layer observed during an airborne lidar flight experiment carried out on 29 January 2021 in the coastal waters near Qionghai city were studied. We employed a hybrid inversion model combining the Klett and perturbation retrieval methods to estimate the seawater optical properties, while the vertical subsurface phytoplankton layer profiles were obtained by an adaptive evaluation. The airborne lidar data preprocessing scheme and inversion of the seawater optical properties were described in detail, and the effects of water environment parameters on the airborne lidar detection performance in coastal waters were discussed. The obtained seawater optical properties and phytoplankton layer profiles exhibit characteristic spatiotemporal distributions. The vertical stratification of seawater optical properties along a flight track from 19.19°N to 19.27°N is more pronounced than that from 19.27°N to 19.31°N. The subsurface phytoplankton layer appears along the flight track at water depths of 5-14 m with a thickness of 2-8.3 m. The high concentrations of chlorophyll, colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) in coastal waters are the main factors leading to the shallower detection depth for airborne lidar. A 532 nm laser emission wavelength is more suitable than 486 nm for investigating coastal waters. The 532 nm receiving channel with 25 mrad receiving field of view achieves a better detection performance than that with 6 mrad. These results indicate that lidar technology has great potential for the wide-range and long-term monitoring of coastal waters.

Satellite Remote Sensing of Water Quality Variation in a Semi-Enclosed Bay (Yueqing Bay) under Strong Anthropogenic Impact

The semi-enclosed bays impacted by heavy anthropogenic activities have weak water exchange and purification capacities. Most of the sea bays have suffered severe eutrophication, water quality deterioration, ecosystem degradation and other problems. Although many countries and local governments have carried out corresponding environmental protection actions, the evaluation of their effectiveness still requires monitoring technology and data support for long-term water environment change. In this study, we take Yueqing Bay, the fourth largest bay in China, as a case to study the satellite-based water quality monitoring and variation analysis. We established a nutrient retrieval model for Yueqing Bay to produce a long-term series of nutrient concentration products in Yueqing Bay from 2013 to 2020, based on Landsat remote sensing images and long-term observation data, combined with support vector machine learning and water temperature and satellite spectra as input parameters, and then we analyzed its spatiotemporal variations and driving factors. In general, nutrient concentrations in the western part of the bay were higher than those in the eastern part. Levels of dissolved inorganic nitrogen (DIN) were lower in summer than in spring and winter, and reactive phosphate (PO4-P) levels were lower in summer and higher in autumn. In terms of natural factors, physical effects (e.g., seasonal variations in flow field) and biological effects (e.g., seasonal differences in the intensity of plankton photosynthesis) were the main causes of seasonal differences in nutrient concentration in Yueqing Bay. Nutrient concentration generally increased from 2013 to 2015 but decreased slightly after 2015. Over the past decade, the economy and industry of Yueqing Bay basin have developed rapidly. Wastewater resulting from anthropogenic production and consumption was transported via streams into Yueqing Bay, leading to the continuous increase in nutrient concentrations (the variation rates: aDIN>0, aPO4−P>0), which directly or indirectly caused high nutrient concentrations in some areas of the bay (e.g., Southwest Shoal at the mouth of Yueqing Bay). After 2015, the various ecological remediation policies adopted by cities around Yueqing Bay have mitigated, to some extent, the increasing nutrient concentration trends (the variation rates: aDIN<0, aPO4−P<0), but not significantly (P > 0.1). The environmental restoration of Yueqing Bay also requires continuous and long-term ecological protection and restoration work to be effective. This research can provide a reference for ecological environment monitoring and remote sensing data application for similar semi-enclosed bays, and support the sustainable development of the bay.