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Although it is widely assumed that business activity is dependent on flows of ecosystem services (ES), little evidence is available with which to evaluate this contention. To address this knowledge gap, we conducted a questionnaire survey of business dependencies on twenty-six different ES in the English county of Dorset, where the environment supports a significant component of the local economy. Responses were received from 212 businesses across twenty-eight sectors. While virtually all businesses (98%) were familiar with the concept of ES, dependency on ES was highly divided with 50% of businesses surveyed claiming no dependence on any ES flows. The highest businesses dependencies reported in this study were for regulating services with the ES of water quality and waste water treatment being of particular importance to businesses. The results however, advised that greater efforts are needed in highlighting the indirect benefits provided by Dorset’s ecosystems, with eight business sectors (58% of respondents) claiming no or little dependence on supporting and habitat services including the ES of biodiversity, habitats for species and maintenance of genetic diversity. Many businesses also indicated little or no dependence on the globally important ES of pollination and soil condition, which may reflect a lack of awareness of dependencies occurring upstream of their value chains. At the sector level, businesses directly involved in protecting, extracting, or manufacturing raw materials were found to be more dependent on provisioning, regulatory and supporting ES than those operating in the service sector who favored cultural ES. These results highlight the value of assessing business dependencies on ES flows, which could usefully inform environmental management and accounting systems and improve monitoring of business performance, and thereby contribute to achievement of sustainability goals.

Carbon capture, utilization, and storage (CCUS) is a gas injection technology that enables the storage of CO2 underground. The aims are twofold, on one hand to reduce the emissions of CO2 into the atmosphere and on the other hand to increase oil/gas/heat recovery. Different types of CCUS technologies and related engineering projects have a long history of research and operation in the USA. However, in China they have a short development period ca. 10 years. Unlike CO2 capture and CO2-EOR technologies that are already operating on a commercial scale in China, research into other CCUS technologies is still in its infancy or at the pilot-scale. This paper first reviews the status and development of the different types of CCUS technologies and related engineering projects worldwide. Then it focuses on their developments in China in the last decade. The main research projects, international cooperation, and pilot-scale engineering projects in China are summarized and compared. Finally, the paper examines the challenges and prospects to be experienced through the industrialization of CCUS engineering projects in China. It can be concluded that the CCUS technologies have still large potential in China. It can only be unlocked by overcoming the technical and social challenges.

The new GHG calculator named SECTOR (Source-selective and Emission-adjusted GHG CalculaTOR for Cropland) is based on the IPCC Tier 2 approach for rice as well as other crops. The new features of SECTOR facilitate high flexibility in terms of entering newly obtained emission factors, easy data transfer from crop statistics for entering activity data and detailed specifications of GHG scenarios. A new procedure of entering frequency-based data on current water management practices was also developed. Moreover, the tool allows deviating from the 2006 IPCC Guidelines by considering field records with high background levels of N₂O emissions in the overall assessment of GHG emissions. This article assesses different applications of the tool, namely as add-ons to field measurements, for GHG calculation at national/sectorial scale and within measurement, reporting and verification of development projects. SECTOR is downloadable in the form of templates that can be used to develop custom versions with varying levels of disaggregated data entries at different scales. A case study for rice production in one Vietnamese province demonstrates the potential to display GHG results in combination with GIS. SECTOR can easily be adjusted to incorporate new emission factors and calculation procedures expected in forthcoming revisions of the IPCC Guidelines.

Abstract Eradicating poverty and mitigating greenhouse gas (GHG) emissions are core issues of global sustainable development goals (SDGs), and China is struggling in realizing these targets. The poverty reduction that leads to popualtion structure and lifestyle changes would have an impact on GHG emission changes. However, few studies have assessed the historical and future impacts of the poverty allevation on China's emissions. Here by linking Chinese Multi-Regional Input Output (MRIO) database to the global MRIO database EXIOBASE, and using provincial household consumption data, we identified the distribution of Chinese household greenhouse gas footprints (HGFs) by income groups in 2015 at the national and provinical levels. Moreover, we focused on the historical impact of poverty alleviation on HGFs during 2010–2015, and developed four scenarios to project future HGFs changes due to poverty alleviation by 2030. We find that eradicating extreme poverty in the secanrio S2, i.e., bringing people to an income above $1.9 daily, does not cause a large emission impact with current technological level. However, lifting people from a higher poverty line of $5.5 per day in the sceanrio S4 results in a 1.6% increase in emissions compared with the scenario S1 without any poverty reduction goals. Furthermore, realizing a higher poverty reduction target will result in an increase of emissions contribution from internatioanl supply chains due to the differences in consumption patterns among different income groups. Our study highlights the conflict between the high poverty alleviaition goal and emission reduciton in China, and reminds us of the need to make more technological efforts for avoiding the large emissions embodied in international supply chains.

AbstractForecasting the variability of dwellings and residential land is important for estimating the future potential of environmental technologies. This paper presents an innovative method of converting average residential density into a set of one-hectare 3D tiles to represent the dwelling stock. These generic tiles include residential land as well as the dwelling characteristics. The method was based on a detailed analysis of the English House Condition Survey data and density was calculated as the inverse of the plot area per dwelling. This found that when disaggregated by age band, urban morphology and area type, the frequency distribution of plot density per dwelling type can be represented by the gamma distribution. The shape parameter revealed interesting characteristics about the dwelling stock and how this has changed over time. It showed a consistent trend that older dwellings have greater variability in plot density than newer dwellings, and also that apartments and detached dwellings have greater variability in plot density than terraced and semi-detached dwellings. Once calibrated, the shape parameter of the gamma distribution was used to convert the average density per housing type into a frequency distribution of plot density. These were then approximated by systematically selecting a set of generic tiles. These tiles are particularly useful as a medium for multidisciplinary research on decentralized environmental technologies or climate adaptation, which requires this understanding of the variability of dwellings, occupancies and urban space. It thereby links the socioeconomic modeling of city regions with the physical modeling of dwellings and associated infrastructure across the spatial scales. The tiles method has been validated by comparing results against English regional housing survey data and dwelling footprint area data. The next step would be to explore the possibility of generating generic residential area types and adapt the method to other countries that have similar housing survey data.

River deltas and estuaries are disproportionally-significant coastal landforms that are inhabited by nearly 600 M people globally. In recent history, rapid socio-economic development has dramatically changed many of the World's mega deltas, which have typically undergone agricultural intensification and expansion, land-use change, urbanization, water resources engineering and exploitation of natural resources. As a result, mega deltas have evolved into complex and potentially vulnerable socio-ecological systems with unique threats and coping capabilities. The goal of this research was to establish a holistic understanding of threats, resilience, and adaptation for four mega deltas of variable geography and levels of socio-economic development, namely the Mekong, Yellow River, Yangtze, and Rhine deltas. Compiling this kind of information is critical for managing and developing these complex coastal areas sustainably but is typically hindered by a lack of consistent quantitative data across the ecological, social and economic sectors. To overcome this limitation, we adopted a qualitative approach, where delta characteristics across all sectors were assessed through systematic expert surveys. This approach enabled us to generate a comparative assessment of threats, resilience, and resilience-strengthening adaptation across the four deltas. Our assessment provides novel insights into the various components that dominate the overall risk situation in each delta and, for the first time, illustrates how each of these components differ across the four mega deltas. As such, our findings can guide a more detailed, sector specific, risk assessment or assist in better targeting the implementation of risk mitigation and adaptation strategies.

Abstract Even though renewable energy development has gained momentum in China, thermal power generation still accounts for approximately 70% of the county's total power generation serving as the major source of carbon dioxide (CO2) emissions in China. Facing the challenges of meeting 2030 peak target of CO2 emission and realizing the coordinated development of thermal power generation in Beijing-Tianjin-Hebei region, this paper applies generalized Divisia Index Method (GDIM) to decompose the dynamics in the relevant CO2 emission. The effects of five factors including electricity demand, energy consumption, technology, energy efficiency and energy-mix are considered. The decomposition suggests that electricity demand is the primary factor driving the CO2 emission up, whereas technology effect decreases CO2 emission the most. Given the significant roles of technology, energy-mix and energy efficiency in CO2 emissions reduction, seven scenarios are designed to identify the optimal coordinated development pathway for thermal power generation in Beijing-Tianjin-Hebei region. Through upgrading energy structure and/or enhancing energy efficiency, the thermal power generation in Beijing-Tianjin-Hebei region can achieve coordinated development and realize the 2030 peak target under four scenarios. The detailed development pathways for CO2 emissions and specific policy implications for Beijing, Tianjin and Hebei are provided to further govern CO2 emissions and maintain sustainable development.