•We calculate the provincial CO2 emissions in China from 2000 to 2012 based on the “apparent energy consumption”.•During 2000 to 2012, Shandong province contributed most to national emissions ...accumulatively.•Provinces located in the northwest and north had higher per capita CO2 emissions and emission intensities.
This study employs “apparent energy consumption” approach and updated emissions factors to re-calculate Chinese provincial CO2 emissions during 2000–2012 to reduce the uncertainty in Chinese CO2 emission estimates for the first time. The study presents the changing emission-socioeconomic features of each provinces as well. The results indicate that Chinese provincial aggregated CO2 emissions calculated by the apparent energy consumption and updated emissions factors are coincident with the national emissions estimated by the same approach, which are 12.69% smaller than the one calculated by the traditional approach and IPCC default emission factors. The provincial aggregated CO2 emissions increased from 3160 million tonnes in 2000 to 8583 million tonnes in 2012. During the period, Shandong province contributed most to national emissions accumulatively (with an average percentage of 10.35%), followed by Liaoning (6.69%), Hebei (6.69%) and Shanxi provinces (6.25%). Most of the CO2 emissions were from raw coal, which is primarily burned in the thermal power sector. The analyses of per capita emissions and emission intensity in 2012 indicates that provinces located in the northwest and north had higher per capita CO2 emissions and emission intensities than the central and southeast coastal regions. Understanding the emissions and emission-socioeconomic characteristics of different provinces is critical for developing mitigation strategies.
Coastal wetlands are crucial to global climate change due to their roles in modulating atmospheric concentrations of greenhouse gases (GHGs) (CO
2
, CH
4
, N
2
O). Under a warming climate, we ...investigated spatial and temporal variations of GHGs emissions over the coastal wetlands in southeastern China during 2012–2014. Five dominant land cover types in coastal wetlands have been considered, including the bare mud flat (BF), the
Spartina alterniflora
flats (SAF), the
Suaeda glauca
flats (SGF), the
Phragmites australis
flat (PAF), and the
Scripus triqueter
flat (STF). The results showed that the annual average CO
2
fluxes were 305.8, 588.8, 370.2, and 136.5 mg m
−2
h
−1
from spring to winter. CH
4
fluxes presented to be a sink in spring (− 0.02 mg m
−2
h
−1
), and functioned as a source in the following seasons. Correlation analysis indicated that the surface air temperature and the cumulative precipitation could be two main factors that influenced the seasonal and inter-annual variations of GHGs emissions. In addition, we provided a regional budget of GHGs emissions that suggested the variations of GHGs emissions under a warming climate.
•Seasonal variations of CO2 and CH4 fluxes were similarly regulated by air temperature.•Spatial variations of the three GHG fluxes were primarily depended on vegetation types.•Effects of tidal flats ...on CH4 and N2O emissions differed with the observation seasons.•The GWP of Spartinaalterniflora among the tidal flats was the highest in the coastal saline wetland.
Coastal saline wetlands are recognized as prominent sources of greenhouse gas emissions. However, insufficient attention has been paid to the effect of coastal wetlands in mitigating global warming caused by greenhouse gases in China. This study aims to investigate how vegetation and soil parameters affect greenhouse gas emissions in a coastal saline wetland. Fluxes of CO2, CH4, and N2O were measured simultaneously in situ using the closed static chamber technique in four different coastal tidal flats, namely, mud flat, Spartina alterniflora flat, Suaeda glauca flat, and grass flat. The measurements were obtained from September 2012 to August 2013 in the Yancheng coastal wetland, southeast China. The average fluxes across all seasons and flats varied from 10.7 to 2297.6mgCO2m−2h−1 (ecosystem respiration), from −0.368 to 4.959mgCH4m−2h−1, and from 1.5 to 65.7μgN2Om−2h−1. Higher CO2 and CH4 fluxes were observed during the summer and autumn seasons. However, the seasonal change of the N2O fluxes was complicated. For the S. alterniflora and grass flats, the highest emissions were observed during summer. For the mud and S. glauca flats, the emissions peaked during winter. The spatial variations of the three greenhouse gas fluxes in the coastal saline wetland primarily depended on vegetation type. The greenhouse gas fluxes from the three tidal flats with vegetation covers (S. alterniflora, S. glauca, and grass flats) were higher than those from the mud flat. Higher CO2 emissions were observed in the S. alterniflora flat than those in the other flats because of the higher carbon sequestration rate, together with higher net primary production and aboveground biomass. However, CH4 and N2O emissions were highest in the grass flat, followed by the S. alterniflora flat. The effects of tidal flats on the CH4 and N2O emissions differed according to the season. The S. alterniflora invasion increased the CO2 emission while slightly lowering the CH4 fluxes, compared with that of native plant communities dominated by Phragmites. Results also suggested that S. alterniflora had the highest global warming potential among the tidal flats in the coastal saline wetland.
Analyses of the spatial and temporal variation of reference evapotranspiration (ET0) and aridity index (AI) can further understand climate change and its effect on hydrology. In this study, based on ...date from 58 standard meteorological stations, the spatio-temporal variations and trends of ET0 and AI were calculated for the Loess Plateau Region (LPR) from 1961 to 2012 using the Mann–Kendall test, the moving t-test, and the Morlet wavelet methods. The results demonstrated: (1) the annual ET0 displayed a statistically significant decrease of −10.3 mm/10 y (P < 0.05) during 1961–2012. At that time, AI also had a decreasing trend of −0.013/10 y over the past 52 years. Compared with ET0, the inter-decadal variations of AI over the LPR seemed to show similar declined trends. (2) Spatially, about 81% stations displayed a decreasing trend for annual ET0 during 1961–2012, and most of them were distributed in the western, northern and southeastern LPR. In addition, about 60% of stations showed statistically decreasing trends for AI, and the major decreases were mainly in the east Qinghai division and northern LPR. (3) Abrupt changes were detected in annual ET0 series in the 1980s and in annual AI series in 1987. Wavelet analysis indicated significant 2 year and non-significant 7, 10 and 14 years in annual ET0 series, and there existed periods of 4, 8 and 12 years for AI. (4) For ET0, wind speed was the most sensitive meteorological factor, followed by sunshine hours, precipitation, and relative humidity. For AI, ET0 and precipitation were the sensitive factors. This study provides an understanding of the effect of recent climate change on hydrological cycle in the LPR.
The invasions of the alien species such as Spartina alterniflora along the northern Jiangsu coastlines have posed a threat to biodiversity and the ecosystem function.Yet,limited attention has been ...given to their potential influence on greenhouse gas（GHG） emissions,including the diurnal variations of GHG fluxes that are fundamental in estimating the carbon and nitrogen budget.In this study,we examined the diurnal variation in fluxes of carbon dioxide（CO_2）,methane（CH_4）,and nitrous oxide（N2O） from a S.alterniflora intertidal flat in June,October,and December of 2013 and April of 2014 representing the summer,autumn,winter,and spring seasons,respectively.We found that the average CH_4 fluxes on the diurnal scale were positive during the growing season while negative otherwise.The tidal flat of S.alterniflora acted as a source of CH_4 in summer（June） and a combination of source and sink in other seasons.We observed higher diurnal variations in the CO_2 and N_2O fluxes during the growing season（1 536.5 mg CO_2 m~（–2） h~（–1） and 25.6 μg N_2O m~（–2） h~（–1）） compared with those measured in the non-growing season（379.1 mg CO_2 m~（–2） h~（–1） and 16.5 μg N_2O m~（–2） h~（–1））.The mean fluxes of CH_4 were higher at night than that in the daytime during all the seasons but October.The diurnal variation in the fluxes of CO_2 in June and N_2O in December fluctuated more than that in October and April.However,two peak curves in October and April were observed for the diurnal changes in CO_2 and N_2O fluxes（prominent peaks were found in the morning of October and in the afternoon of April,respectively）.The highest diurnal variation in the N_2O fluxes took place at 15：00（86.4 μg N_2O m~（–2） h~（–1）） in June with an unimodal distribution.Water logging in October increased the emission of CO_2（especially at nighttime）,yet decreased N_2O and CH_4 emissions to a different degree on the daily scale because of the restrained diffusion rates of the gases.The seasonal and diurnal variations of CH_4 and CO_2 fluxes did not correlate to the air and soil temperatures,whereas the seasonal and diurnal variation of the fluxes of N_2O in June exhibited a significant correlation with air temperature.When N_2O and CH_4 fluxes were converted to CO_2-e equivalents,the emissions of N_2O had a remarkable potential to impact the global warming.The mean daily flux（MF） and total daily flux（TDF） were higher in the growing season,nevertheless,the MF and TDF of CO_2 were higher in October and those of CH_4 and N_2O were higher in June.In spite of the difference in the optimal sampling times throughout the observation period,our results obtained have implications for sampling and scaling strategies in estimating the GHG fluxes in coastal saline wetlands.
To evaluate the controlling factors for coastline change of the Changjiang (Yangtze River) Estuary since 1974, we extracted the mean high tide line from multi-temporal remote sensing images that span ...from 1974 to 2014 at 2-year intervals. We chose 42 scenes to constrain the changing pattern of the Changjiang Estuary coastline, and implemented GIS technology to analyze the area change of the Changjiang (Yangtze) Subaerial Delta. Runoff, sediment discharge and coastal engineering were withal considered in the analysis of the coastline changes. The coastline has transgressed seaward since 1974, and a part of it presents inter-annual variations. The area of the Changjiang Subaerial Delta increased by 871 km
2
, with a net accretion rate of 21.8 km
2
/a. Based on the change of sediment discharge due to the major projects in the Changjiang River Basin, we divided the changing pattern of the coastline into three stages: the slow accretion stage (1974–1986), the moderate accretion stage (1987–2002), and the rapid accretion stage (2003–2014). Liner regression analysis illustrated that there is a significantly positive correlation between the area changes and sediment discharge in the Chongming Eastern Shoal and Jiuduansha. This suggested that sediment load has a fundamental effect on the evolution of the Changjiang Estuary. Construction of Deep Waterway in the North Passage of the Changjiang River (1998–2010) led to a rapid accretion in the Hengsha Eastern Shoal and Jiuduansha by influencing the hydrodynamics in North Passage. Coastal engineering such as reclamation and harbor construction can also change the morphology of the Changjiang Estuary. We defined a contribution rate of area change to assess the impact of reclamation on the evolution of Changjiang Estuary. It turned out that more than 45.3% of area increment of the Changjiang Estuary was attributed to reclamation.
Based on data from the Datong hydrological station and 147 meteorological stations, the influences of climate change and human activities on temporal changes in water discharge and sediment load were ...examined in the Yangtze River basin from 1953 to 2010. The Mann–Kendall test, abrupt change test (Mann–Kendall and cumulative anomaly test), and Morlet wavelet method were employed to analyze the water discharge and sediment load data measured at the Datong hydrological station. The results indicated that the annual mean precipitation and water discharge exhibited decreasing trends of −0.0064mm/10yr and −1.41×108m3/yr, respectively, and that the water sediment load showed a significant decreasing trend of −46.5×106t/yr. Meanwhile, an abrupt change in the water discharge occurred in 2003. The sediment load also exhibited an abrupt change in 1985. From 1970 to 2010, the climate change and human activities contributed 72% and 28%, respectively, to the water discharge reduction. The human-induced decrease in the sediment load was 914.03×106t/yr during the 1970s and 3301.79×106t/yr during the 2000s. The contribution from human activities also increased from 71% to 92%, especially in the 1990s, when the value increased to 92%. Climate change and human activities contributed 14% and 86%, respectively, to the sediment load reduction. Inter-annual variations in water discharge and sediment load were affected by climate oscillations and human activities. The effect of human activities on the sediment load was considerably greater than those on water discharge in the Yangtze River basin.
Display omitted
•Quantitative assessments of climate and human activity are very important for the further understanding of estuarine and delta evolution.•In recent decades, the decrease in sediment load has mainly been caused by human activities, especially dam construction.•The effects of human activities on sediment load have increased over time.
With the Rise of Central China Plan, the central region has had a great opportunity to develop its economy and improve its original industrial structure. However, this region is also under pressure ...to protect its environment, keep its development sustainable and reduce carbon emissions. Therefore, accurately estimating the temporal and spatial dynamics of CO2 emissions and analysing the factors influencing these emissions are especially important. This paper estimates the CO2 emissions derived from the fossil fuel combustion and industrial processes of 18 central cities in China between 2000 and 2014. The results indicate that these 18 cities, which contain an average of 6.57% of the population and 7.91% of the GDP, contribute 13% of China's total CO2 emissions. The highest cumulative CO2 emissions from 2000 to 2014 were from Taiyuan and Wuhan, with values of 2268.57 and 1847.59 million tons, accounting for 19.21% and 15.64% of the total among these cities, respectively. Therefore, the CO2 emissions in the Taiyuan urban agglomeration and Wuhan urban agglomeration represented 28.53% and 20.14% of the total CO2 emissions from the 18 cities, respectively. The three cities in the Zhongyuan urban agglomeration also accounted for a second highest proportion of emissions at 23.51%. With the proposal and implementation of the Rise of Central China Plan in 2004, the annual average growth rate of total CO2 emissions gradually decreased and was lower in the periods from 2005 to 2010 (5.44%) and 2010 to 2014 (5.61%) compared with the rate prior to 2005 (12.23%). When the 47 socioeconomic sectors were classified into 12 categories, “power generation” contributed the most to the total cumulative CO2 emissions at 36.51%, followed by the “non-metal and metal industry”, “petroleum and chemical industry”, and “mining” sectors, representing emissions proportions of 29.81%, 14.79%, and 9.62%, respectively. Coal remains the primary fuel in central China, accounting for an average of 80.59% of the total CO2 emissions. Industrial processes also played a critical role in determining the CO2 emissions, with an average value of 7.3%. The average CO2 emissions per capita across the 18 cities increased from 6.14 metric tons in 2000 to 15.87 metric tons in 2014, corresponding to a 158.69% expansion. However, the average CO2 emission intensity decreased from 0.8 metric tons/1000 Yuan in 2000 to 0.52 metric tons/1000 Yuan in 2014 with some fluctuations. The changes in and industry contributions of carbon emissions were city specific, and the effects of population and economic development on CO2 emissions varied. Therefore, long-term climate change mitigation strategies should be adjusted for each city.
Based on daily precipitation dates at 42 meteorological stations in the Pearl River Basin, the spatial and temporal changes in precipitation index are analyzed during 1960-2012, eleven indices of ...precipitation extremes are studied. The results show that wet day precipitation, consecutive wet days and numbers of heavy precipitation days exhibit non-significant decreasing trends in the study area. Consecutive dry days and simple daily intensity index have increased and are significant at the 95% level, while other extreme precipitation indexes have non-significant increasing trends. Spatial changes of precipitation extreme indices show obvious differences, and they are not clustered either. On the whole, the number of rainy days has decreased over the Yunnan-Guizhou Plateau and hilly Guangxi, and the spatial distribution reflects the regional climatic complexity. Continuous wavelet transform analysis indicates that there are significant periodic variations with periods of similar to 7 and similar to 14 years in extreme precipitation, and that there is also a 6-year period and a 14-year period with the Pacific Decadal Oscillation (PDO) and Southern Oscillation Index (SOI), respectively, which are very consistent. The PDO and SOI are important influential factors for precipitation. In addition, except for consecutive dry days, the other extreme precipitation indices have significant correlations with annual precipitation. Large scale atmospheric circulation changes derived from NCEP/NCAR reanalysis reveals that a strengthening anticyclonic circulation, increasing geopotential height, weakening monsoonal flow, and vapor transportation over the Eurasian continent have contributed to the changes in precipitation extremes in southern China.
•An integrated ecosystem health assessment mechanism for coastal area is proposed.•Total suspended matter, nutrients, and heavy metals are major environmental factors influencing ecological ...health.•Species abundance, diversity, and evenness are major community factors influencing ecological health.•Several different health states are divided by the value of eco-exergy indicators.•Environmental and community factors are related to eco-exergy indicators, respectively.
The main objective of ecosystem health management is to preserve the capacity of ecosystems to respond to disturbances and future changes. We proposed a set of ecological indicators for coastal ecosystem health assessment using physical stressors such as total suspended matter, chemical stressors including nutrients and heavy metal pollutants, community structure metrics including species richness, diversity and evenness, and ecosystem level eco-exergy indicators. The results of our case study indicate that the health status of the Jiangsu coastal ecosystem is limited by environmental stressors and factors that affect the community species diversity. The health status of nektonic and benthic communities is reflected by water quality and sediment physicochemical properties, respectively. The results of our case study demonstrate that the integrated ecological health indicator system can provide a comprehensive assessment that corresponds with the current health of coastal ecosystems and a reliable theoretical basis for regional coastal management.
PDF
