New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors

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

Methodology and applications of city level CO2 emission accounts in China

China is the world's largest energy consumer and CO2 emitter. Cities contribute 85% of the total CO2 emissions in China and thus are considered as the key areas for implementing policies designed for climate change adaption and CO2 emission mitigation. However, the emission inventory construction of Chinese cities has not been well researched, mainly owing to the lack of systematic statistics and poor data quality. Focusing on this research gap, we developed a set of methods for constructing CO2 emissions inventories for Chinese cities based on energy balance table. The newly constructed emission inventory is compiled in terms of the definition provided by the IPCC territorial emission accounting approach and covers 47 socioeconomic sectors, 17 fossil fuels and 9 primary industry products, which is corresponding with the national and provincial inventory. In the study, we applied the methods to compile CO2 emissions inventories for 24 common Chinese cities and examined uncertainties of the inventories. Understanding the emissions sources in Chinese cities is the basis for many climate policy and goal research in the future

The impact of climate change and urban growth on urban climate and heat stress in a subtropical city

Urban residents face increasing risk of heat stress due to the combined impact of climate change and intensification of the urban heat island (UHI) associated with urban growth. Considering the combined effect of urban growth and climate change is vital to understanding how temperatures in urban areas will change in the future. This study investigated the impact of urban growth and climate change on the UHI and heat stress in a subtropical city (Brisbane, Australia) in the present day (1991–2000) and medium term (2041–2050; RCP8.5) during summer. A control and urban growth scenario was used to compare the temperature increase from climate change alone with the temperature increase from climate change and urban growth. Average and minimum temperatures increased more with climate change and urban growth combined than with climate change alone, indicating that if urban growth is ignored, future urban temperatures could be underestimated. Under climate change alone, rural temperatures increased more than urban temperatures, decreasing the effect of the UHI by 0.4 °C at night and increasing the urban cool island by 0.8 °C during the day. With climate change, the number of hot days and nights doubled in urban and rural areas in 2041–2050 as compared to 1991–2000. The number of hot nights was higher in urban areas and with urban growth. Dangerous heat stress, defined as apparent temperature above 40 °C, increased with climate change and occurred on average 1–2 days every summer during 2041–2050, even in shaded conditions. There was higher temperature increases with urban growth and climate change than with climate change alone, indicating that reducing the effect of the UHI is vital to ensuring urban growth does not increase the heat stress risks that urban residents will face in the future

Accumulation, temporal variation, source apportionment and risk assessment of heavy metals in agricultural soils from the middle reaches of Fenhe River basin, North China

The Fenhe River basin is the main agricultural and industrial developed area in Shanxi province, China. In recent years, agricultural non-point source pollution in the Fenhe River basin intensified, threatening soil quality and safety in the area. Accumulation of eight heavy metals (HMs) including chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), lead (Pb) and mercury (Hg) has been detected in soil samples from 50 agricultural sites (0-20 cm) from the middle reaches of the Fenhe River basin. The ecological and human health risk and potential sources of the eight HMs were investigated. In addition, the human health and ecological risks imposed by the possible sources of the eight HMs were quantitatively apportioned. The enrichment factor (EF) values of Cr, Ni, Cu, Pb and Zn were lower than 2, indicating minimal enrichment, while values for As, Cd and Hg were between 2 and 5, exhibiting moderate enrichment. Temporal variation analysis suggested that most HMs in the study area exhibited low concentrations after 2015, except As. The potential ecological risk index was 174.09, indicating low ecological risk. The total hazard index and cancer risk values were 0.395 and 5.35 x 10(-4) for adults and 2.75 and 3.63 x 10(-4) for children, indicating the accepted standard levels were exceeded for non-carcinogenic risk for children and carcinogenic risks for both adults and children. Four potential sources were identified: (1) natural sources, (2) farming activities, (3) coal combustion, and (4) exhaust emissions. Natural sources represented the largest contributor to ecological risk, accounting for 57.42% of the total. Coal combustion was the major contributor to human health risks, accounting for 43.27% and 43.73% of the total non-carcinogenic risk and carcinogenic risk for adults, respectively, and 42.72% and 43.88% for children, respectively

Geographical classifications to guide rural health policy in Australia

The Australian Government's recent decision to replace the Rural Remote and Metropolitan Area (RRMA) classification with the Australian Standard Geographical Classification - Remoteness Areas (ASGC-RA) system highlights the ongoing significance of geographical classifications for rural health policy, particularly in relation to improving the rural health workforce supply. None of the existing classifications, including the government's preferred choice, were designed specifically to guide health resource allocation, and all exhibit strong weaknesses when applied as such. Continuing reliance on these classifications as policy tools will continue to result in inappropriate health program resource distribution. Purely 'geographical' classifications alone cannot capture all relevant aspects of rural health service provision within a single measure. Moreover, because many subjective decisions (such as the choice of algorithm and breakdown of groupings) influence a classification's impact and acceptance from its users, policy-makers need to specify explicitly the purpose and role of their different programs as the basis for developing and implementing appropriate decision tools such as 'rural-urban' classifications. Failure to do so will continue to limit the effectiveness that current rural health support and incentive programs can have in achieving their objective of improving the provision of health care services to rural populations though affirmative action programs