Spatiotemporal analysis of the food-related carbon emissions of China: Regional heterogeneity and the urban‒rural divide.

As the world's largest carbon emitter of food systems, China's goal of carbon neutrality cannot be achieved without addressing the issue of food GHGs. Given the knowledge gap in subnational spatiotemporal research on China's food carbon emissions, especially drivers of regional heterogeneity and the urban‒rural divide, this study uses the household metabolism approach, the gray correlation, and logarithmic mean Divisia index decomposition to assess food-related carbon emissions (FCEs) in China, conducts urban‒rural comparisons and quantifies emission drivers across 31 provinces/regions from 1990 to 2022. The data are sourced from authentic and credible government departments. The results indicate a notable increase in FCEs in most provinces for urban regions following periods of slight decline (1990-2001), sharp increase (2001-2016), and slow growth (2016-2022). In contrast, there has been a more pronounced increase in most provinces for rural regions following a phase of slow growth (1990-2002), a marked decline (2002-2012), and a sharp rise (2012-2022). Among others, per capita carbon emissions from plant-based foods decreased from 345.79 kg in 1990 to 262.70 kg in 2022, whereas emissions from animal-based foods increased from 90.78 kg to 284.39 kg over the same period, suggesting that dietary changes have been a major contributor. Clustering based on the gray correlation further confirms the large interprovincial heterogeneity and significant urban‒rural divide. Regardless of cluster and stage, affluence consistently and significantly drives the growth of FCEs in urban/rural areas, whereas food consumption intensity consistently and significantly contributes to this reduction. The Engel coefficient reduces carbon emissions by a large amount, and the carbon emission factor increases urban/rural FCEs, albeit by a small amount. Consumption willingness reduces FCEs in urban areas but increases FCEs in rural areas in most stages. These findings can aid policy-makers in designing emission reduction policies tailored to the local context.

Review on Eco-Environment Research in the Yellow River Basin: A Bibliometric Perspective.

The Yellow River Basin (YRB) is an important economic zone and ecological barrier in China. The analysis of its research characteristics and hotspots has been helpful to grasping the future research direction. This work carried out text mining and analysis on scientific papers related to eco-environment research in the YRB from English and Chinese publications. It showed that: there was a fluctuating upward trend over the past 30 years, which was closely related to major events in the YRB during the same period. Chinese research institutions have a closer cooperation with the USA, Australia and other developed countries. More articles were from high-quality journals in ecology, the environment, and others. Interestingly, research institutions with more Chinese articles were mainly located around Beijing or the YRB. Additionally, from a research object perspective, both the English and Chinese articles have mainly focused on large areas such as the lower Yellow River, the middle reaches of the Yellow River, and the upper reaches of the Yellow River, then turning to small areas such as the Yellow River estuary and the source area of the Yellow River. Eco-environment research in the YRB has involved multiple disciplines, and "water-soil-vegetation-ecological protection" has been widely concerned. From the evolution law of hot topics, it has shown a transformation from quantity to quality, from utilization to management, from macro to micro, from construction to high-quality development. It suggests that future research should focus on water, soil, the ecological environment and local high-quality development in small regions and small watersheds.

Testing the impact of first-mover advantage on household energy-related carbon emissions: an exploratory study from six urban agglomerations in China.

The household sector has become the second-largest source of energy consumption and CO2 emissions in China. It is important to understand the trends and changing mechanisms of household energy-related CO2 emissions (HECEs) in different social stages for mitigating the impact of climate change. However, the existing trends in HECEs and whether they are congruent with the expectation that HECEs in later developed areas are lower than those in priority areas under the same economic level are unclear. Here, we compared the per capita HECEs (PHECEs) of urban agglomerations under the same economic standards and analyzed the causes of the comparative results. We find that (1) HECEs increased rapidly from 3.65 × 108 t to 12.42 × 108 t during 1995-2017, with an average annual growth rate of 14.19%; (2) urban agglomerations that developed earlier do not have higher PHECEs. The PHECEs of urban agglomerations with moderate and later development do not decrease under increased social, technological, and cognitive conditions; (3) carbon intensity (CI), energy intensity (EI), and per capita regional gross domestic product (PCG) have a positive impact on PHECEs, and the potential impact of EI on PHECEs reduction is greater; (4) the effects of CI, EI, and PCG on PHECEs in different urban agglomerations are various. However, these effects are similar within urban agglomerations. Our study provides a reference for reducing CO2 emissions in the household sector and for the green development of urban agglomerations and emphasizes that the growth of HECE at a reasonable level is necessary when technology does not meet sufficient constraints.

A critical assessment of provincial-level variation in agricultural GHG emissions in China.

China is a world leader on agriculture production; with only 8% of global cropland it feeds 20% of the world's population. However, the increasing production capacity comes with the cost of greenhouse gas (GHG) emissions. As a populous country with the highest GHG emissions in the world, determining how to achieve the dual goals of mitigating climate change and ensuring food security is of great significance for the agricultural sector. This requires assessing the spatial variation in agricultural greenhouse gases (GHGs) and their drivers. In this study, we conduct a spatial assessment of agricultural GHGs at the provincial level in China for the years 1997-2017, and then explore the effects of related factors on GHG emissions using a geographically weighted regression (GWR) model. The results suggest the following. 1) There have always been significant interprovincial variations, whether in the total amount, structure, intensity, or per capita level of agricultural GHG emissions. 2) The directions of the effects of selected factors on GHG intensity fall broadly into three categories: negative effects (urbanization, intensity of agricultural practices, and agricultural structure), positive effects (agricultural investment and cropland endowments), and mixed effects, with factors leading to reductions in some provinces and increases in others (economic level, frequency and intensity of disasters, and the level of mechanization). 3) The magnitude of the effects varies by factor and also by province. The results suggest synergetic province- or state-specific reduction policies in agricultural GHG for China, as well as for other developing and emerging economies.

Investigating the spatiotemporal variability and driving factors of China's building embodied carbon emissions.

Rapid and large scale construction activities consume significant resources and make impacts on the environment. To support policy for emission reduction and route of low-carbon society development, this paper estimated building stocks and building embodied carbon emissions (BECEs) in China's 31 provinces from 1997 to 2016 by material flow analysis (MFA). Furthermore, global and local Moran's indices were employed to investigate the geographical clustering patterns, and temporal and spatial decomposition models were proposed to identify the driving forces. The results reveal the total BECEs has boomed from 9.67 billion tons in 1997 to 28.99 billion tons in 2016. BECEs in 31 provinces have experienced consistent increase but obvious differences in growth rate, and are spatially inclined to decrease from eastern coastal regions to western inland regions. The change of spatial agglomeration pattern is complex and variable. It presents that a long and narrow "H-L agglomeration" is located in the two northernmost provinces and the other 29 provinces enforce a sequence arrangement with an order of "H-H", "L-H", "H-L", and "L-L" from east to west. Temporal decomposition results show that investment scale, economic level, and population density are the main driving forces for the increase of BECEs from both national and provincial levels, while the main reasons for the decrease are technical level and return on investment. Spatial decomposition results demonstrate that population density and provincial area are the main driving forces for the difference between provincial and national average, and others cause the difference among provinces.

Household CO2 Emissions: Current Status and Future Perspectives.

The household sector, which plays a critical role in emission reduction, is a main source of greenhouse gas (GHG) emissions. Although numerous academic journals have published papers on household CO2 emissions (HCEs), great challenges remain in research on assessments, determinants, and further research prospects. This work reviews and projects HCEs using a bibliometric analysis and a systematic review based on the data from the Web of Science (WOS) platform from 1991 to 2020. Over the last 30 years, there has been a rapid and active trend of research on HCEs. We find that (1) the scale of the bibliometric analysis shows that research on HCEs is interdisciplinary and must consider overall cognition of the environment, the economy, society, and technology. It also needs to strengthen cooperation between different countries/territories to emphasize the quality and influence of papers on HCEs. (2) A review of previous literature shows that research on HCEs mainly focuses on the research object, mainstream assessments, and influencing factors. The following six main aspects impact HCEs: demographic, income, social, technological, policy, and natural factors. (3) The research discussion suggests that more micro-level research needs to be conducted, such as research on the city level and the individual level, which is important for sustainable development and low consumption. A comparative analysis of the differences in HCEs is a future research direction. Additionally, localized carbon emission reduction measures need to be implemented.

Health and Economic Loss Assessment of PM2.5 Pollution during 2015-2017 in Gansu Province, China.

Many studies have reported that air pollution, especially fine particulate matter (PM2.5), has a significant impact on health and causes economic loss. Gansu Province is in the northwest of China, which is a typical economically underdeveloped area. However, few studies have evaluated the economic loss of PM2.5 related to health effects in this province. In this study, a log-linear exposure-response function was used to estimate the health impact of PM2.5 in 14 cities in Gansu Province from 2015 to 2017, and the amended human capital (AHC) and cost of illness (COI) method were used to evaluate the related economic loss caused by the health impact from PM2.5. The results show that the estimated total number of health endpoints attributed to PM2.5 pollution were 1,644,870 (95%CI: 978,484-2,215,921), 1,551,447 (95%CI: 917,025-2,099,182) and 1,531,372 (95%CI: 899,769-2,077,772) in Gansu Province from 2015 to 2017, respectively. Correspondingly, the economic losses related to health damage caused by PM2.5 pollution were 42,699 (95%CI: 32,380-50,768) million Chinese Yuan (CNY), 43,982 (95%CI: 33,305-52,386) million CNY and 44,261 (95%CI: 33,306-52,954) million CNY, which were equivalent to 6.45% (95%CI: 4.89%-7.67%), 6.28% (95%CI: 4.75%-7.48%), and 5.93% (95%CI: 4.64%-7.10%) of the region Gross Domestic Product (GDP) from 2015 to 2017, respectively. It could be seen that the proportions of health economic loss to GDP were generally high, although the proportion had a slight downward trend. The economic loss from chronic bronchitis and all-cause mortality accounted for more than 94% of the total economic loss. The health impact, economic loss and per capita economic loss in Lanzhou, the provincial capital city of Gansu, were obviously higher than other cities from the same province. The economic loss in Linxia accounted for the highest proportion of GDP. The health impacts in the Hexi region, including the cities of Jiuquan, Jiayuguan, Zhangye, Jinchang and Wuwei, were generally lower, but the economic loss and per capita economic loss were still higher. We also found that urbanization and industrialization were highly correlated with health economic loss caused by PM2.5 pollution. In conclusion, the PM2.5-related health economic burden in Gansu Province was serious. As an economically underdeveloped region, it was very important to further adopt rigid and effective pollution control policies.

Green technology innovation development in China in 1990-2015.

Patent data present a number of advantages compared to other alternative measures of innovation. This paper presents research on the use of environmentally relevant technology patent data using a comprehensive analysis method to analyze the development of green technology innovation in China in 1990-2015. From the analysis, it can be concluded that during the period of 2000-2015, China's environmental-related technology innovation made great progress and was at the forefront of green technology growth; in particular, the areas of water and wastewater treatment, solar photovoltaic (PV) energy, lighting, improvements related to bulk or fine chemicals or pharmaceuticals, electric vehicles, and other technologies made great achievements. These technologies are closely related to environmental policies, such as climate change mitigation and green industry transformation, for which China has been advocating for more than a decade. However, after analyzing China's green development, it was found that, although some of the indicators, environmental-related patents, and green developments have made great progress, complete reliance on green technology is far off in the future.

Dynamism of household carbon emissions (HCEs) from rural and urban regions of northern and southern China.

China contributes 23 % of global carbon emissions, of which 26 % originate from the household sector. Due to vast variations in both climatic conditions and the affordability and accessibility of fuels, household carbon emissions (HCEs) differ significantly across China. This study compares HCEs (per person) from urban and rural regions in northern China with their counterparts in southern China. Annual macroeconomic data for the study period 2005 to 2012 were obtained from Chinese government sources, whereas the direct HCEs for different types of fossil fuels were obtained using the IPCC reference approach, and indirect HCEs were calculated by input-output analysis. Results suggest that HCEs from urban areas are higher than those from rural areas. Regardless of the regions, there is a similarity in per person HCEs in urban areas, but the rural areas of northern China had significantly higher HCEs than those from southern China. The reasons for the similarity between urban areas and differences between rural areas and the percentage share of direct and indirect HCEs from different sources are discussed. Similarly, the reasons and solutions to why decarbonising policies are working in urban areas but not in rural areas are discussed.

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China.

Given the large expenditures by households on goods and services that contribute a large proportion of global CO2 emissions, increasing attention has been paid to household CO2 emissions (HCEs). However, compared with industrial CO2 emissions, efforts devoted to mitigating HCEs are relatively small. A good understanding of the effects of some driving factors (i.e., urbanization rate, per capita GDP, per capita income/disposable income, Engel coefficient, new energy ratio, carbon intensity, and household size) is urgently needed prior to considering policies for reducing HCEs. Given this, in the study, the direct and indirect per capita HCEs were quantified in rural and urban areas of China over the period 2000-2012. Correlation analysis and gray correlation analysis were initially used to identify the prime drivers of per capita HCEs. Our results showed that per capita income/disposable income, per capita GDP, urbanization rate, and household size were the most significantly correlated with per capita HCEs in rural areas. Moreover, the conjoint effects of the potential driving factors on per capita HCEs were determined by performing principal component regression analysis for all cases. Based on the combined analysis strategies, alternative polices were also examined for controlling and mitigating HCEs growth in China.