Understanding the spatial disparity in socio-economic recovery of coastal communities following typhoon disasters.

The increasing risk of climate change in the Anthropocene underscores the importance and urgency of enhancing resilience to climate-related disasters. However, the assessment of resilience to disasters with traditional statistical data is spatially inexplicit and timeliness inadequate, and the determinants of resilience remain unclear. In this study, we employed spatially detailed daily nighttime light images to assess socio-economic disturbance and track near real-time recovery of coastal communities in Southeast China following super typhoon Meranti. Furthermore, we constructed a "exposure-sensitivity-adaptive capacity" framework to explore the role of key factors in shaping spatiotemporal patterns of recovery. Our case study showed a significant spatial disparity in socio-economic recovery in the post-typhoon period. Low-urbanized areas recovered relatively rapidly with the weakest socio-economic disturbance they suffered, and middle-urbanized areas experienced the slowest recovery despite the disruption being moderate. Remarkably, high-urbanized areas were the most severely impacted by the typhoon but recovered fast. The exposure to hazard, socio-economic sensitivity, and adaptive capacity in communities explained well the spatial disparity of resilience to the typhoon. Maximum wind speed, percentage of the elderly, and percentage of low-income population significantly negatively correlated with resilience, whereas commercial activity intensity, spatial accessibility of hospitals, drainage capacity, and percentage of green open space showed significantly positive relationships with resilience. Notably, the effects of key factors on resilience were spatially heterogeneous. For instance, maximum wind speed exhibited the strongest influence on resilience in middle-urbanized areas, while the effect of commercial activity intensity was most pronounced in low-urbanized areas. Conversely, spatial accessibility of hospitals and drainage capacity showed the strongest influence in high-urbanized areas. Our study highlights the necessity of linking post-disaster recovery with intensity of hazard, socio-economic sensitivity, and adaptive capacity to understand community resilience for better disaster risk reduction.

Assessing Agricultural Livelihood Vulnerability to Climate Change in Coastal Bangladesh.

The adverse impacts of climate change exert mounting pressure on agriculture-dependent livelihoods of many developing and developed nations. However, integrated and spatially specific vulnerability assessments in less-developed countries like Bangladesh are rare, and insufficient to support the decision-making needed for climate-change resilience. Here, we develop an agricultural livelihood vulnerability index (ALVI) and an integrated approach, allowing for (i) mapping out the hot spots of vulnerability distribution; (ii) identifying key factors of spatially heterogeneous vulnerability; and (iii) supporting intervention planning for adaptation. This study conceptualized vulnerability as a function of exposure, sensitivity, and adaptive capacity by developing a composite index from a reliable dataset of 64 indicators comprising biophysical, agro-ecological, and socioeconomic variables. The empirical studies of coastal Bangladesh revealed that Bhola, Patuakhali, and Lakshmipur districts, around the mouth of the deltaic Meghna estuaries, are the hot spot of vulnerability distribution. Furthermore, the spatially heterogeneous vulnerability was triggered by spatial variation of erosion, cyclones, drought, rain-fed agriculture, land degradation, soil phosphorus, crop productivity, sanitation and housing condition, infant mortality, emergency shelters, adoption of agro-technology. The integrated approach could be useful for monitoring and evaluating the effectiveness of adaptation intervention by substituting various hypothetical scenarios into the ALVI framework for baseline comparison.

Identifying the trade-offs between climate change mitigation and adaptation in urban land use planning: An empirical study in a coastal city.

Cities play a significant role in climate change mitigation and adaptation. Urban land planning shapes the urban form and is considered to be an effective approach for climate change mitigation and adaptation. Yet, there is little knowledge about what urban forms can reduce both greenhouse gas (GHG) emissions and climate stresses while considering trade-offs between them. Here, we investigate the role of urban land use in both climate change mitigation and adaptation. In particular, we assess quantitatively the competition between strategies for mitigation and adaptation and identify potential win-win solutions in land use responses. Using a coastal city as a case study, we find that the land use strategies for unilateral mitigation or adaptation can cause contradicting consequences with respect to the reductions in GHG emissions and climate stresses, i.e. reductions in GHGs could increase climate stresses or vice versa. Poorly integrated strategies potentially may compromise international efforts to meet the Climate Action in the Sustainable Development Goals. Properly integrated mitigation and adaptation strategies, or climate-sensitive land use planning, however, can lead to win-win outcomes and eventually achieve co-benefits. Yet, any co-benefits will gradually diminish if there is a delay in climate-sensitive land use planning, implying growing GHGs and intensified climate stresses. Our analysis indicates that integrating climate change mitigation and adaptation in urban land use needs to be enacted as soon as possible: any delays in implementation reduce the window to act to maximize the co-benefits.

Transforming nitrogen management of the urban food system in a food-sink city.

Nitrogen flows in urban food systems are attracting increasing concern. However, characteristics of nitrogen flow and systematic measures to reduce reactive nitrogen losses in the food systems of consumption-oriented cities in developing countries have not been well understood, especially in a quantitative way. This study empirically investigates the transforming nitrogen flows of an urban food system in a food-sink city in China, with a nitrogen metabolism model. Three types of nitrogen loads transfer are identified: from production to consumption side, between different environmental media, and from areas within to areas beyond the city boundary. By integrating sensitivity analysis into the metabolism model, increases in the sewage treatment rate, the sewage nitrogen removal rate, and the ratio of animal excreta returned to field are found to contribute the most to the water nitrogen load reduction, and reducing food waste at the consumer level is the most influential measure for lowering soil nitrogen loads, under the existing nitrogen flow regime. Additionally, a three-tier template framework is proposed to streamline city strategies (prevention, abatement, recycling, regional cooperation, etc.) for reducing the N loads of urban food systems, providing references for sustainable nutrient management in urban ecosystems.

Chinese cropping systems are a net source of greenhouse gases despite soil carbon sequestration.

Soil carbon sequestration is being considered as a potential pathway to mitigate climate change. Cropland soils could provide a sink for carbon that can be modified by farming practices; however, they can also act as a source of greenhouse gases (GHG), including not only nitrous oxide (N2 O) and methane (CH4 ), but also the upstream carbon dioxide (CO2 ) emissions associated with agronomic management. These latter emissions are also sometimes termed "hidden" or "embedded" CO2 . In this paper, we estimated the net GHG balance for Chinese cropping systems by considering the balance of soil carbon sequestration, N2 O and CH4 emissions, and the upstream CO2 emissions of agronomic management from a life cycle perspective during 2000-2017. Results showed that although soil organic carbon (SOC) increased by 23.2 ± 8.6 Tg C per year, the soil N2 O and CH4 emissions plus upstream CO2 emissions arising from agronomic management added 269.5 ± 21.1 Tg C-eq per year to the atmosphere. These findings demonstrate that Chinese cropping systems are a net source of GHG emissions and that total GHG emissions are about 12 times larger than carbon uptake by soil sequestration. There were large variations between different cropping systems in the net GHG balance ranging from 328 to 7,567 kg C-eq ha-1  year-1 , but all systems act as a net GHG source to the atmosphere. The main sources of total GHG emissions are nitrogen fertilization (emissions during production and application), power use for irrigation, and soil N2 O and CH4 emissions. Optimizing agronomic management practices, especially fertilization, irrigation, plastic mulching, and crop residues to reduce total GHG emissions from the whole chain is urgently required in order to develop a low-carbon future for Chinese crop production.

Investigating the comparative roles of multi-source factors influencing urban residents' transportation greenhouse gas emissions.

The current growth in transportation-related greenhouse gas (GHG) emissions has been largely attributed to rapid urbanization, particularly for cities in developing countries. Studies on the contributing factors and analysis of the mechanisms by which they influence transportation GHG emissions could aid in better achievement of mitigation goals. Yet, comparative contributions of the different sources of these drivers have not been well quantitatively investigated. This study employs a wide range of indicators across urban form, socio-demographic characteristics and residents' travel attitudes. By integrating a questionnaire-based survey of 1125 household in 45 communities in Xiamen City, China, land-use-based urban form quantification, inventory-based GHG calculation, a path analysis model is built to identify the interactions among these indicators and investigate their comparative direct and indirect effects on residents' local transportation GHG emissions. It was found that many variables interactively influence the transportation GHG emissions, producing considerable effects, both direct and indirect. Urban form plays a leading role in transportation GHG emissions, in comparison to socio-demographics and travel attitudes. Population density, land use mix, road connectivity and bus accessibility, in urban form; education, in socio-demographics; and willingness to ride the bus, in travel attitudes; were found to have significant positive effects on reducing residents' local transportation GHG emissions. Urban density-characterized by population density here-is the primary influential factor, due not only to its large direct effects, but also to its wide indirect effects through its influence on other variables. The results of this study may help policy makers consider how they can effectively utilize these key indicators to formulate mitigations in the transportation sector, and particularly, how to design low-carbon-friendly urban forms, in urban planning.

[Dynamics and environmental load of food carbon consumption during urbanization: a case study of Xiamen City, China].

With the rapid urbanization, city plays a more and more significant role in the carbon cycle of urban ecosystem. The contribution of household food carbon consumption to urban carbon cycle has become increasingly important, and has been the hot issues of the urban carbon cycle study. We analyzed the dynamics of the food carbon consumption in Xiamen City from 1988 to 2010, evaluated and forecasted the trends of food carbon consumption and its environmental load. The results showed that, from 1988 to 2010, per capita food consumption and per capita food carbon consumption declined by 6% and 25%, respectively. However, due to the rapid growth of population, the total food consumption and total food carbon consumption increased by 116% and 70%, respectively. The rising of total food carbon consumption led to the increasing environmental load of food carbon. The environmental load of food carbon increased from 98 800 t to 166 200 t, particularly there is a dramatic increase of carbon input into soil in recent years. From 2011 to 2024, total food carbon consumption and environmental load will continue to rise and then decline in 2025. Per capita food carbon consumption will decline continuously from 2011. The analysis of household food consumption showed that per household food carbon consumption was affected by household income, food cost and household persons. High food carbon consumption household usually had in average three persons eating at home, spent in average 3 125 yuan x month(-1) on food, the per household food carbon consumption was 1 134.91 kg,and the per capita food carbon consumption was 378.30 kg. Per capita food carbon consumption of high-consumption family was 4.84 times higher than that of low-consumption family.

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China.

Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 - 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 - 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.