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Atmospheric pollution caused by particulate matter (PM), which has been identified as a carcinogen, is a major concern in South Korea, with various PM emission sources identified, including vehicles and power plants. The Korean government recently announced plans to increase research and development (R&amp, D) expenditure to reduce PM levels in the atmosphere. In this study, the research topics and research networks for PM technology are summarized to help policymakers to more efficiently plan future R&amp, D investment. A topic model is implemented to identify the main keywords from Science Citation Index (SCI) papers related to PM, and social network analysis is used to understand research collaboration between different countries or institutions. The results reveal that China and the USA published the largest number of SCI papers related to PM research, while South Korea was ranked in the top five globally. Unlike China and South Korea, developed countries such as the USA, Germany, and France have been carrying out PM research on climate change, ozone, NH3, nanoparticles, and the health effects on pregnant women. The primary research networks are centered on China and the USA, while South Korea has weak collaboration with other countries or institutions. More effort is thus required to improve strategic R&amp, D investment and the research network within Korea.

The construction industry is recognized as a major cause of environmental pollution, and it is important to quantify and evaluate building energy. As interest in big data has increased over the past 20 years, research using big data is active. However, the links and contents of much literature have not been summarized, and systematic literature studies are insufficient. The objective of this study was a holistic review of building energy efficiency/reduction based on big data. This review study used a holistic analysis approach method framework. As a result of the analysis, China, the Republic of Korea, and the USA had the most published papers, and the simulation and optimization area occupied the highest percentage with 33.33%. Most of the researched literature was papers after 2015, and it was analyzed because many countries introduced environmental policies after the 2015 UN Conference on Climate Change. This study can be helpful in understanding the current research progress to understand the latest trends and to set the direction for further research related to big data.

There is an increasing concern about fossil energy and products derived from it. The plastic industry depends on oil, and produced plastics cannot degrade naturally. An alternative to plastics from oil is the use of bioplastics, which can be degradable. The bibliometric study of the publications related to bioplastics carried out in this paper shows that research on this topic is growing both in developed (USA, European Union, and Canada) and in developing countries (China, India, Thailand, and Malaysia), mostly following the implementation of bioeconomy standards and labels by their governments. The main authors and the collaborations they have worldwide are also presented here. The research carried out in this paper is not only devoted to technological aspects but also to economic aspects and inhabitant ratios. Trends in publications, by country and authors, are analyzed. Finally, this paper also studies the countries governmental policies and how they impact the bioplastic field. The authors at the University of Lleida would like to thank the Catalan Government for the quality accreditation given to their research group GREiA (2017 SGR 1537). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia.

On the background of climate change, studying tourism eco-efficiency of cities is of great significance to promote the green development of tourism. Based on the panel data of the three major urban agglomerations in China&rsquo, s Yangtze River Delta, Pearl River Delta, and Beijing&ndash, Tianjin&ndash, Hebei region from 2008 to 2017, this paper constructed an evaluation index system and measured the tourism eco-efficiency of 63 cities by using a hybrid distance model called Super-EBM (epsilon-based measure). We compared the spatial and temporal evolution characteristics of tourism eco-efficiency in the three urban agglomerations. Furthermore, the internal factors influencing tourism eco-efficiency were explored through input&ndash, output redundancy, and the external factors were analyzed by a panel regression model. The results indicate that the tourism eco-efficiency of the three urban agglomerations in China generally shows a decreasing-rising-declining trend. Among them, the Yangtze River Delta has the highest eco-efficiency, followed by the Pearl River Delta, and the lowest in the Beijing&ndash, Hebei region. Moreover, there is a certain gap within each urban agglomeration. The redundancy input of labor and capital is the main internal cause of low eco-efficiency. Among the external factors, the status of the tourism industry and the level of urbanization have a positive effect on eco-efficiency, while the level of tourism development, technological innovation and investment have a negative impact on it. In the future, we must attach great importance to the development quality and overall benefit value of the tourism industry so as to achieve green and balanced development of the three major urban agglomerations in eastern China. Based on the above conclusions, this paper puts forward targeted policy implications to improve the tourism eco-efficiency of cities.

In recent years, a noticeable contradiction has emerged between the disorderly sprawl and fragile climate environment of many cities, especially in mountainous cities. Therefore, this paper respectively constructed evaluation indicators for urban sprawl sustainability (USS) and climate change adaptability (CCA). Next, a coupling coordination degree model was used to measure the coordinated development of USS and CCA. Finally, this paper analyzed the coordinated development type of USS and CCA in the Chongqing metropolitan area from 2007 to 2017. The results of this paper show that USS and CCA have gradually shifted to coordinated development in the Chongqing metropolitan area during the study period. However, there were obvious regional differences in the type of coordinated development in the Chongqing metropolitan area. The coordinated development degree of USS and CCA in nine districts ranged from 0.635 to 0.721 in 2017. It can be divided into three types: slightly coordinated development with lagging CCA, slightly coordinated development with lagging USS, and moderately coordinated development with lagging CCA. Those districts should give priority to the use of Nature-Based Solutions (NBS), and multi-center and multi-group approaches to enhance the coordinated development between USS and CCA, which is also helpful for mountainous cities in China and other countries.

Due to the large-scale utilization of high-carbon fossil energy, considerable amounts of critical air pollutants (CAPs) and greenhouse gas (GHG) have been emitted, which has led to increasingly serious global climate change and local air pollution problems. Given that climate change and air pollution have the same source, energy systems, the rational development and use of energy for collaborative governance should be emphasized to solve these problems in parallel. This paper presents a multi-dimensional, multi-perspective and achievable analysis framework to quantitatively evaluate the emission reduction effects of energy countermeasures aimed at tackling climate change and governing air pollution in support of sustainable development. As a typical developing country pursuing sustainable development, China is taken as an example to demonstrate an application of the proposed framework to assess the emission reduction effects of energy countermeasures issued for tackling climate change and governing air pollution on CAPs and GHG. The results indicate that the key energy actions proposed in this paper would result in emission reductions of approximately 6 million tons (Mt) of CAPs and 575 Mt of GHG in 2016. By 2020 and 2030, emission reductions of 12 Mt of CAPs and 1094 Mt of GHG and of 21 Mt of CAPs and 1975 Mt of GHG, respectively, will be achieved. The proposed framework can effectively help China identify the emissions reduction effect of a given energy countermeasure and support the development of policy describing the next steps for tackling climate change and haze pollution. The proposed framework in this paper is also beneficial for countries similar to China in their efforts to simultaneously address climate change and improve air quality.

International trade shifts production of a large amount of carbon dioxide (CO2) emissions embodied in traded goods from the importing country to the exporting country. The European Union (EU) plays a prominent role in the flow of international-related emissions as it accounts for the second largest share of global exports and imports of goods. Consumption-based accountings (CBA) emerged as alternative to the traditional emission inventories based on the Intergovernmental Panel on Climate Change (IPCC) guidelines. According to the IPCC criteria, countries where products are consumed take no responsibility for the emissions produced by exporter countries, thus neglecting the emissions embodied in trade. By taking this aspect into account, CBA are considered of great importance in revealing emissions attributed to the final consumer. Using a CBA approach, this paper evaluates the impact of international trade in the EU in terms of CO2 emissions, looking both at the internal trade flows within the EU-28 and at the external trade flows between the EU and the rest of the world during the period 2012&ndash, 2015. We find that the EU is a net importer of emissions as its emissions due to consumption exceed those due to production. In particular, in 2015 the ratio between import- and export-embodied emissions was more than 3:1 for the EU-28 that imported 1317 Mt CO2 from the rest of the world (mainly from China and Russia) while exporting only 424 Mt CO2. Concerning emissions flows among EU countries, Germany represents the largest importer, followed by the UK. To get a deeper understanding on possible environmental implications of Brexit on UK emission responsibilities, the paper also advances a few hypotheses on how trade flows could change based on the existing trade patterns of the UK. Data analysis shows that a 10% shift of UK imports from EU partners to its main non-EU trading partners (India, China, and US) would increase its emission responsibility by 5%. The increase in UK emission responsibility would more than double (+11%) in case of a 30% shift of UK imports. Similar results would apply if UK replaced its current EU partners with its main Commonwealth trading partners as a result of Brexit.

In order to tackle climate change and build a low-carbon economy, China has selected seven provinces and cities as carbon trading pilots and plans to establish the national emissions trading scheme (ETS) in 2017. However, since China has not yet reached peak carbon emissions, and as a major developing country, the conflict between increasing energy demand and the requirement to reduce emissions brings challenges to the design of a national ETS suitable for China’s development. In this paper, we summarize the current situation of China’s seven ETS pilots with respect to coverage, allowance allocation, transactions, punishment mechanisms and especially the market performance. By analyzing the common practice of three international mandatory schemes, combined with China’s current circumstances and characteristics of market construction and regulation, we emphasize China’s own economic reality, and propose several recommendations for building a suitable and effective national ETS. This paper could provide new perspectives towards scheme design for China and other similar countries.

As a significant energy consumer, China is under tremendous pressure from the international community to address climate change issues by reducing carbon emissions, thus, the use of clean energy is imperative. Wind power is an essential source of renewable energy, and improving the efficiency of wind power generation will contribute substantially to China’s ability to achieve its energy-saving and emission reduction goals. This paper measured the wind power efficiency of 30 provinces in China from 2012 to 2017 using the data envelopment analysis (DEA) method. Moran’s I index and the spatial Durbin model were applied to analyse the spatial distribution of the wind power efficiency and the spatial effects of influencing factors. The results show obvious differences in the spatial distribution of wind power efficiency in China, specifically, the wind power efficiency in the eastern and western regions is higher than that in the central areas. Moreover, wind power efficiency has a significant positive spatial correlation between regions: the eastern and western regions show certain high-high clustering characteristics, and the central area shows certain low-low clustering characteristics. Among the influencing factors, the fixed asset investment and carbon emission intensity of the wind power property have a negative impact on the efficiency of regional wind power production, while the urbanization process and carbon emission intensity have significant spatial spillover effects. The optimization of the economic structure, technological innovation and the construction of energy infrastructure are expected to improve the regional wind power efficiency. The results present a new approach for accurately identifying the spatial characteristics of wind power efficiency and the spatial effects of the influencing factors, thus providing a reference for policymakers.

Based on the monthly observation data of major surface meteorological observatories in Northwest China from 1960 to 2019, this paper uses the temperature and humidity index (THI), wind efficiency index (WEI), and clothing index (ICL) to construct a comprehensive climate comfort index evaluation model. This model was used to quantitatively evaluate the change characteristics of climate comfort in Northwest China against the background of climate warming. The results show that the overall climate comfort index in Northwest China is on the rise. In terms of space, an increase in the climate comfort index means an increase in the comfort zone, with the largest increase in the southeastern part of Gansu Province and the southern part of Shaanxi Province. The trend of change is that the increase in the north is greater than that in the south, and the higher the latitude, the greater the change. The space range of the comfort zone and the sub-comfort zone is generally expanding, and the climate is gradually becoming more comfortable. In terms of time, an increase in the climate comfort index means an increase in the climate comfort period, and the annual comfort index shows an increasing trend. The comfort period is mostly distributed in summer, with the most suitable cities in May and September, followed by June.

Exploring precipitation threshold from an economic loss perspective is critical for rainstorm and flood disaster risk assessment under climate change. Based on the daily gridded precipitation dataset and direct economic losses (DELs) of rainstorm and flood disasters in the mainland of China, this paper first filtered a relatively reasonable disaster-triggering daily precipitation threshold (DDPT) combination according to the relationship between extreme precipitation days and direct economic loss (DEL) rates at province level and then comprehensively analyzed the spatial landscape of DDPT across China. The results show that (1) the daily precipitation determined by the combination of a 10 mm fixed threshold and 99.3th percentile is recognized as the optimal DDPT of rainstorm and flood disasters, and the correlation coefficient between annual extreme precipitation days and DEL rates reached 0.45 (p < 0.01). (2) The optimal DDPT decreases from southeast (up to 87 mm) to northwest (10 mm) across China, and the DDPTs of 7 out of 31 provinces are lower than 25 mm, while 5 provinces are higher than 50 mm on average. These results suggest that DDPTs exist with large spatial heterogeneity across China, and adopting regional differentiated DDPT is helpful for conducting effective disaster risk analysis.

The China–US trade conflict will inevitably have a negative impact on China’s trade imports and exports, industrial development, and economic growth, and will affect the achievement of climate change goals. In the short term, the impact of the trade conflict on China’s import and export trade will cause the carbon emissions contained in traded commodities to change accordingly. To assess the impact of the trade conflict on China’s climate policy, this paper combines a model from the Global Trade Analysis Project (GTAP) and the input–output analysis method and calculates the carbon emissions in international trade before and after the conflict. The conclusions are as follows: (1) The trade war has led to a sharp decline in China–US trade, but for China as a whole, imports and exports have not changed much, (2) China’s export emissions have changed little, its import emissions have dropped slightly, and its net emissions have increased, and (3) China’s exports are still concentrated in energy-intensive industries. Changes in trade will bring challenges to China’s balancing of climate and trade exigencies. China–US cooperation based on energy and technology will help China cope with climate change after the trade conflict.

Climate change poses unprecedented challenges for humanity. Reducing carbon intensity is an inevitable choice for tackling climate change and promoting sustainable development. China has made some emission reduction commitments in the international community to promote the decoupling of China&rsquo, s economic development from carbon emissions. The realization of the industrial structure from the &ldquo, single-wheel drive&rdquo, of the manufacturing to the &ldquo, two-wheel drive&rdquo, economic development model of the service industry and the manufacturing has become a key measure to achieve China&rsquo, s economic intensive development. According to resource misallocation situation in different regions, this paper explored the impact of the collaborative agglomeration between producer services and manufacturing (hereinafter referred to as industrial co-agglomeration) on carbon intensity. The research results show that the carbon intensity is decreasing year by year, and the degree of intensification of China&rsquo, s economic growth continues to increase. Moreover, the effect of industrial co-agglomeration to promote carbon emission reduction is significantly limited by the degree of misallocated resources, and there is a double threshold effect. Specifically, in areas where resource allocation is reasonable, industrial co-agglomeration can produce significant agglomeration effects and promote carbon intensity reduction. Once the degree of misallocated resources exceeds a threshold level, the agglomeration effect will turn into a crowding effect, resulting in an inability to reduce carbon intensity. We comprehensively analyzed the driving factors for reducing carbon intensity and proposed policy pathways for achieving China&rsquo, s carbon intensity target.

This paper proposes an index-based assessment tool to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change, and to aggregate these opinions into intuitive and comparable graphs. This tool enables cities to measure and monitor the multiple factors that contribute to their resilience towards climate risk and hazard in the long term. We applied this tool to five key infrastructure sectors in six representative cities in the Yangtze River Delta region. The graphs generated provide for the first time first-hand insights into the aggregative understanding of various stakeholders with regard to the current and future climate risk in their concerned sectors and cities. Our results indicate that a high level of exposure is not automatically associated with a high level of vulnerability across our selected cities. While all cities need to make efforts to reduce their vulnerability towards climate hazards, those characterized by &ldquo, lower level of exposure but higher level of vulnerability&rdquo, need to make more urgent and much greater efforts.

To respond to the adverse impact of climate change on agricultural total factor productivity, the question of how to adopt actively appropriate strategies is particularly critical for the stakeholders. However, the previous researchers have paid more attention to investigating the measure methods, regional differences, and determinants of Chinese agricultural total factor productivity, but the possible impact of climate change factors like rainfall, temperature, and evaporation on regional agricultural total factor productivity in China have not yet received the attention that they deserve. Furthermore, more importantly, the study on how to take active measures to reduce and mitigate the negative effects from climate change is relatively small. Therefore, in allusion to the above-mentioned problems, using the data envelopment analysis and building a spatial panel data model embedded with climate change factors, this paper calculated Chinese agricultural total factor productivity and then explored the possible impact of climate change on regional agricultural total factor productivity at a provincial level in China. Results mainly show that the impact of some factors, like annual total precipitation, average temperature in the growing season, and evaporation intensity on regional agricultural total factor productivity, are all very significant and negative, which suggests that the more precipitation, the higher the temperature is, and the higher evaporation intensity would lower agricultural total factor productivity in China. Furthermore, in order to response to mitigate the adverse effects from climate change on agricultural total factor productivity, local governments should continue to increase financial support for the local agricultural economic development, because this action could be beneficial for the related stakeholders in improving agricultural total factor productivity. Summing up, our evidence study would provide an important basic theory basis in terms of increasing agricultural total factor productivity and promoting regional agricultural economic development in China.

Spring maize (Zea mays L.) is a thermophilic C4 crop which is sensitive to climate change. This paper provides a detailed assessment of the effect of climate change on the crop from a new perspective, by predicting the probability of the potential distribution of spring maize across China. The affected area of spring maize suitability was identified, and then the affected area was subdivided into the improved area and the deteriorated area. Our results confirmed that there was a detrimental consequence for spring maize suitability under observed climate change from 1961&ndash, 1990 to 1981&ndash, 2010. However, our results revealed that warming scenarios of 1.5 &deg, C and 2 &deg, C were helpful for the suitable area expansion of spring maize. The affected area was smaller under warming scenarios than under historical climate change, revealing that temperature rise alone was not enough to trigger a &ldquo, tipping point&rdquo, (a threshold value after which abrupt shifts occur) for spring maize, even if warming is 2 &deg, C above the level of 1961&ndash, 1990. Our results not only benefit China in the design of mitigation and adaptation strategies, but also provide a theoretical judgement that the impact of global warming on the crop ecosystem is not serious if other climate factors remain unchanged.

Passenger transport has become a significant producer of carbon emissions in China, thus strongly contributing to climate change. In this paper, we first propose a model of ecological pressure of the carbon footprint in passenger transport (EPcfpt). In the model, the EPcfpt values of all the provinces and autonomous regions of China are calculated and analyzed during the period of 2006–2015. For the outlier EPcfpt values of Beijing, Shanghai and Tianjin, the research areas are classified into two scenarios: the first scenario (all the provinces and autonomous regions) and the second scenario (not including Beijing, Shanghai and Tianjin). The global spatial autocorrelation analysis of the first scenario shows that the EPcfpt might be randomly distributed, while it shows positive spatial autocorrelation in the second scenario. Furthermore, we carry out the local spatial autocorrelation analysis of the second scenario, and find that the low aggregation areas are the most common type and are mainly located in the west of China. Then the disparities in EPcfpt between China’s Eight Comprehensive Economic Zones are further analyzed. Finally, we put forward a number of policy recommendations in relation to the spatio-temporal changes and the regional disparities of EPcfpt in China. This study provides related references for proposing effective policy measures to reduce the ecological pressure of carbon emissions from the passenger transport sector.

Since 2005, China has become the largest emitter of CO2. The transport sector is a major source of CO2 emissions, and the most rapidly growing sector in terms of fuel consumption and CO2 emissions in China. This paper estimated CO2 emissions in the transport sector across 30 provinces through the IPCC (International Panel on Climate Change) top-down method and identified the spatiotemporal pattern of the decoupling of transport CO2 emissions from economic growth during 1995 to 2016 by the modified Tapio&rsquo, s decoupling model. The CO2 emissions in the transport sector increased from 103.10 million ton (Mt) in 1995 to 701.04 Mt in 2016. The year, 2005, was a turning point as the growth rate of transport CO2 emissions and the intensity of transport CO2 emissions declined. The spatial pattern of transport CO2 emissions and its decoupling status both exhibited an east-west differentiation. Nearly 80% of the provinces recently achieved decoupling, and absolute decoupling is beginning to take place. The local practices of Tianjin should be the subject of special attention. National carbon reduction policies have played a significant role in achieving a transition to low-carbon emissions in the Chinese transport sector, and the integration of multi-scale transport CO2 reduction policies will be promising for its decarbonisation.

With the increasingly severe global environment and climate change, the growing social attention toward the environmental problems has prompted local governments to make policy adjustments. The formulation of the carbon emission right allocation scheme is important for policy-makers. Many researchers have studied the problem of carbon emission right allocation by using data envelopment analysis (DEA) models. However, the existing literature using traditional models consider each Decision-Making Unit (DMU) as a &ldquo, black box&rdquo, without taking the internal structure into account, but in fact, it is more accurate for formulating the scheme when considering the inner operation of DMUs. This paper investigates the allocation plan of carbon emission right among each province in China from 2007&ndash, 2016 based on a two-stage DEA model. The results indicate that, first, there is no space for carbon emission in the north, northeast, and northwest from 2007&ndash, 2016, while in the southern regions, it always exists. In addition, the carbon emission permits of the southern and eastern regions are increasing, but in the southwestern regions, the carbon emission space barely fluctuated during this decade. Second, the potential of carbon emission reduction of each region tends to be stable after 2014, and in the north and northwest, it fluctuated greatly from 2007&ndash, 2016. Besides, the northwest region has had the potential of emission reduction since 2010, while it also exists in the northern region after 2014.

Globalization has been on everyone’s lips in light of the contemporary conditions. It has been viewed mostly as a stage reached as a result of long-term societal changes over the course of world history. For us, globalization has been an ongoing process for at least the last 5000 years. Little attention has been paid to the socioeconomic and natural processes that led to the current transformation. With the exception of historical sociologists, there is less interest in examining the long-term past as it is often assumed that the past has nothing to teach us, and it is the future that we have to turn our intellectual gaze. This paper will argue the opposite. We believe a long-term tracing of the socioeconomic and political processes of the making of the modern world will allow us to have a more incisive understanding of the current trajectory of world development and transformations. To plead our case, we outline the emergence of the first Eurasian World Economy linking seven regions (Europe, the Arabian Peninsula, East Africa, the Persian Gulf, Central Asia, South Asia, Ceylon, Southeast Asia, and China) of the world, with the exception of the Americas, starting as early as 200 BC, and the sequence of structural crises and transformations (trading networks and commodities) that has circumscribed the structures and trends of the current global system. Such consideration in our view is limited if we do not also include the relations between social systems and Nature, and the rhythms of the climate. For the latter, an awareness of the natural rhythms of the climate as well as human induced changes or climate forcing have triggered system-wide level collapses during certain early historical periods.