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The transfer and driving factors of industrial embodied wastewater in China's interprovincial trade
Abstract
Currently, interprovincial trade and the industrial division of labor in China are rapidly developing. The end users of products are not responsible for their wastewater discharge but indirectly transfer their own wastewater discharge to production locations through trade flows. This undoubtedly exacerbates the burden of environmental governance at production locations and results in the unreasonable sharing of discharge reduction responsibility between production and consumption areas of products. Studies that focus on the embodied wastewater transfer caused by interprovincial trade and its drivers are important for the formulation of equitable emission reduction targets and environmental policies. Therefore, based on the multiregional input-output (MRIO) model and structural decomposition analysis (SDA), this paper analyzes the transfer and driving factors of industrial embodied wastewater in interprovincial trade in China at the interprovincial and industrial sector levels. The results demonstrate that the transfer volume of industrial embodied wastewater increased from 5,423,884,700 tons in 2012 to 6,343,801,700 tons in 2015 in Chinese interprovincial trade, at a growth rate of 16.96%. The regions with industrial embodied wastewater net outflows were mainly located in eastern regions with a more well-developed manufacturing industry such as Shandong and Jiangsu, the net inflow areas were mainly concentrated in central and western regions such as Chongqing, Sichuan and Yunnan. From the perspective of the industrial sector, the chemical industry, papermaking and printing and manufacturing industry of cultural items, education resources and sports goods, and food manufacturing and tobacco processing industry were the three key sectors regarding the inflow and outflow of embodied wastewater in trade. Through SDA, it was found that the growth of the economic scale was the main reason for the outflow of industrial embodied wastewater in the various provinces. The technology effect imposed a negative influence on the transfer of industrial embodied wastewater in most provinces, especially in Henan and Guangxi. In the short term, technology improvements can be employed to reduce the transfer volume of industrial embodied wastewater, but in the long term, industrial structure optimization and upgrading are required to reduce the discharge and transfer of industrial embodied wastewater. Therefore, to reduce water pollution and control industrial wastewater discharge, it is necessary to consider the transfer and main driving factors of embodied wastewater caused by interprovincial trade when assigning environmental governance responsibilities to each province.
... In addition to being transmitted directly through natural water bodies, water pollution can also be transmitted indirectly through economic activities (Wiedmann and Lenzen 2018;Sun et al. 2021). Through the exchange of goods and services, inter-regional trade can transfer the pollutant discharges associated with consumption in importing regions to exporting regions (Wu and Ye 2020). ...
... For example, Wu and Ye (2020) applied the MRIO approach to estimate the transfer of gray water footprints induced by China's domestic trade in 2012. Using structural decomposition analysis (SDA), Sun et al. (2021) further investigated the drivers of China's trade-related industrial wastewater from 2012 to 2015. These studies have demonstrated that China's economic trade results in the transfer of water pollutant discharges from wealthier regions to less developed provinces (Li et al. 2017;Wang et al. 2018). ...
... Overall, coastal developed provinces like Shanghai, Beijing, Jiangsu, and Guangdong were shown to have a net outflow of water pollution, while Jiangxi, Guangxi, Hebei, and Guizhou were the top recipients of water pollution. This may be explained by the differences in water endowment, industrial structure, and consumption patterns (Sun et al. 2021). The flow patterns of COD, NH 3 -N, and WPE were mainly characterized by a net flow from wealthier provinces (e.g., Beijing, Shanghai, and Jiangsu) to less developed ones (e.g., Hebei, Guangxi, and Jiangxi). ...
Transboundary water pollution induced by inter-regional trade is a complex and challenging issue due to the multiple jurisdictions involved. This study combined water pollution discharge inventory, multi-regional input–output analysis, discharge responsibility-sharing, and ecological compensation model to advance the collaborative control of water pollution embodied in China’s inter-provincial trade. Over a fifth of China’s water pollution discharges in 2017, equivalent to 1376 Kt, were a result of inter-provincial trade, which primarily flowed from wealthier coastal provinces to less developed ones. Moreover, the analysis demonstrates a mismatch between economic gains and environmental costs. In particular, Jiangxi and Guangxi bear the greatest environmental impact (64 and 58 Kt, respectively) while only receiving meager economic returns (131 and 80 billion Yuan). The economic benefit shared responsibility results for the great majority of provinces fell between production- and consumption-based discharges, and this compromise-based allocation of responsibility is more likely to gain acceptance across various regions. Provinces such as Shanghai, Jiangsu, and Beijing necessitate the highest compensation volumes to others, with 31 Kt, 25 Kt, and 20 Kt, respectively, while provinces including Guangxi, Jiangxi, and Ningxia require the largest inflows of compensation, totaling 26 Kt, 23 Kt, and 18 Kt, respectively. The compensation outcomes ensure that less developed regions, bearing a greater pollution burden, receive compensation from more developed regions with lower pollution burdens. The compensation values aligned with compensation volumes, with a few exceptions driven by variations in shadow prices of water pollution. Our study sheds light on the inter-provincial water pollution burdens and benefits and provides a quantitative basis for optimizing the responsibility-sharing and compensation strategies in China, thereby promoting regional cooperation on water pollution control.
... Given the complexity of processing technology and the high processing cost of industrial wastewater pollution (Jabeen et al. 2015), reducing industrial wastewater discharge is more important from a practical perspective than its treatment. Due to this, numerous governments worldwide have implemented various effective measures to reduce industrial wastewater discharge (Keiser and Shapiro 2019;Sun et al. 2021). For instance, the Clean Responsible Editor: Philippe Garrigues Hui Guo and Yawen Zhang have contributed equally to this paper. ...
... The types of EKC are U and N types expressing that industrial wastewater discharge is increasing with economic growth (Murshed et al. 2021). This finding suggests that the pollution driven by the discharge of industrial wastewater from these cities is owing to effective measures to improve the pollution promptly (Sun et al. 2021). Thus far, these cities need to formulate relevant policies to control water pollution and achieve green development in accordance with environmental changes (The People's Government of Sichuan Province 2021b). ...
In this study, we used spatial autocorrelation, Environmental Kuznets Curve (EKC), and Logarithmic Mean Divisia Index model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116,580 to 42,064.96 million tons as observed from the Moran index ranging from -0.310 to 0.302. We identified that the EKC type of Sichuan province was monotonically decreasing and six types of the EKC (monotonically decreasing, monotonically increasing, U, N, inverted U, and inverted N, shape) in 18 major cities. The technical effect (from -0.0964 to -8.8912) can reduce the discharge of industrial wastewater, while the economy effect (0.2948–5.882), structure effect (0.0892–4.5183), and population effect (from -0.0059 to 0.2873) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and changed from non-significant dissociation to non-significant agglomeration to non-significant dissociation during the study period. Furthermore, technical management upgrade is the primary driver in Sichuan province to reduce industrial wastewater discharge during this period.
... According to the Tapio decoupling model, the decoupling states were divided into eight types with the corresponding classification criteria, shown in Table 2. The integration of the decoupling analysis method with the Logarithmic Mean Divisia Index (LMDI) model enhances the examination of the putative drivers behind fluctuations in carbon dioxide emissions [23,[45][46][47][48][49]. The results derived from both the additive and multiplicative decompositions of the LMDI model and indicators were found to be consistent. ...
This study comprehensively assessed carbon dioxide emissions over a span of two decades, from 2000 to 2020, with the decomposition and decoupling analyses considering multiple influence factors across both short-term and long-term dimensions. The results revealed great fluctuations in the decoupling analysis index (DAI) for subjected sectors such as natural resource processing, electricity, gas, water, textiles, machinery, and electronics manufacturing. Of note, significantly changed sectoral DAIs were observed in urban traffic and transportation, logistics warehousing, and the postal industry within Anhui Province. In contrast, the DAIs of other sectors and social services exhibited a weak decoupling state in Anhui Province. The industrial sectors responsible for mining and textiles and the energy structure encompassing electricity, gas, and water emerged as the primary contributors to carbon dioxide emissions. Additionally, the efficiency of the socio-economic development (EDE) was identified as the principal driver of carbon dioxide emissions during the observed period, while the energy consumption intensity (ECI) served as the putative crucial inhibiting factor. The two-dimensional decoupling of carbon dioxide emissions attributable to the EDE demonstrated a gradual transition from industrial sectors to buildings and tertiary industries from 2000 to 2020. In the future, the interaction between urban carbon dioxide emissions and the socio-economic landscape should be optimized to foster integrated social sustainable development in Anhui Province.
... Compared to the two previously mentioned methods, the IO theory-based SDA method performs better in the mechanism analysis of the final demand-side influencing factors . Therefore, it is widely used to examine the drivers of pollution emissions and resource consumption in regions and sectors (Wang et al 2016, Mi et al 2017, Sun et al 2021. In terms of WF research, Yang et al (2015) and Feng et al (2015) combined the IO model and the SDA method to explore WF and its drivers in Beijing and Zhangye City, respectively. ...
Water scarcity has become the most significant limiting factor for sustainable economic and social development in the Yellow River Basin (YRB). Despite this, most current studies on water resources in the YRB from a water footprint (WF) perspective have focused on WF measurements and have explored the influencing factors of WF changes in certain industries, while the impact mechanisms driving regional WF changes remain unclear. To bridge this research gap, the WF of nine provinces in the YRB for 2012 and 2017 were quantified using an environmentally extended multi-regional input-output model (EE-MRIO), and the driving forces of regional WF changes were explored via structural decomposition analysis (SDA). The results showed that the WF of the YRB increased by 3.8% to 113.64 billion m3 between 2012 and 2017. With rapid economic development and enhanced inter-regional trade links, the external WF has played an important role in meeting local water demand. Technological advances and production structure adjustments contribute to the reduction of the WF, thus promoting the sustainable use and management of the YRB's water resources. Both consumption patterns and final demand per capita have dominated the YRB's WF growth, particularly in the economically developed middle and lower reaches, where urban household consumption drove the largest WF, accounting for over 40%. Therefore, in the future, continuous optimization of the consumption structure and guidance of green consumption awareness are expected to contribute more to the reduction in WF. The findings of this study reveal the primary causes of WF changes in the YRB and offer a theoretical justification for the formulation of water conservation and sustainable utilization policies.
... With the use of environmental accounting, it is essential to uncover the underlying socioeconomic driving factors of interregional trade so that targeted policies can be proposed. For instance, Sun et al. (2021) pointed out that scale effect and technology effect were the main factors of interregional trade on the embodied industrial water in China. Wang et al. (2022) found that production structure, consumption structure, and trade volume were key factors on interregional trade between Heilongjiang and other provinces. ...
Large-scaled interregional trade is based upon massive exchanges of natural resources, leading to more environmental emissions and economic imbalance. China is the largest trade country in the world and has to face such challenges since different Chinese provinces are in different development stages with different resource endowments. By using the latest multi-regional input–output (MRIO) tables and exergy accounting, this study aims to investigate natural resources and added values embodied in interregional trade in China for years of 2012, 2015, and 2017. Regional environmental inequality (REI) index and logarithmic mean Divisia index (LMDI) were applied to measure the imbalance states and uncover corresponding driving factors. Results show that the total trade volumes in the middle Yellow River and eastern coastal regions were generally higher than those in other regions, together accounting for 41.50 ~ 41.78% of the total trade volume during the study period. The major flows of embodied natural resources shifted from the middle Yellow River region to western coastal, eastern coastal, and southern coastal regions. The northern coastal and eastern coastal regions were the major exporters of embodied added value. Less developed regions had higher REI values, indicating more environmental and economic losses than developed regions. Natural resources intensity was the major impact factor on the trade imbalances in most provinces. This study provides valuable insights for alleviating trade imbalance and promoting sustainable natural resources management based on cross-regional collaboration.
... To explore the drivers of carbon transfer, research methods usually include Structural Decomposition Analysis (SDA) [50][51][52], Index Decomposition Analysis (IDA) [53,54], and Geographically Weighted Regression (GWR) models [55,56], etc. The former two methods are more mainstream for analyzing energy consumption and air pollution emission drivers; the latter, as an extension of traditional regression, is widely applied to the fields of environmental, social, economic, and earth science, etc. ...
To understand the embodied carbon transfer in China’s domestic trade from 2007 to 2017 and its driving forces, we quantitatively measured the embodied carbon transfer among 30 provinces by using the Multi-regional input-output (MRIO) model, explored the temporal and spatial evolutionary features of the interprovincial embodied carbon emission transfer by using spatial autocorrelation, and further revealed its drivers using the Geographical Detector Model for the first time. We find that: (1) Based on the producer and consumer accounting principles, the amount of embodied carbon emissions of each province has increased, and there are huge differences. (2) The number of provinces with net embodied carbon emissions transfer is increasing, to 18 in 2017 and the target provinces are mostly energy-rich regions, such as Shanxi, Xinjiang, and Inner Mongolia, which have a severe “carbon leakage” phenomenon with developed coastal provinces. (3) The scale and spatial distribution of net carbon transfer out shows a characteristic of “high in the north and low in the south”, and the tendency of net transfer from the less developed provinces to the developed regions is becoming more and more obvious. (4) The global differences in the promoting factors of the net embodied carbon transfer are not prominent, but the differences at the local scale are significant, with energy intensity and environmental regulation playing an increasingly significant role. Therefore, it is recommended to strengthen low-carbon technology innovation and environmental regulation, increase the percentage of renewable energy consumption, accelerate the mobility of various resource factors, and improve energy utilization efficiency.
... The wastewater footprint is a more complex indicator compared to the previously derived indicators for direct, indirect and cumulative wastewater discharges. This is because it also includes international virtual wastewater flows that are included in foreign trade exchanges [63,64]. In this context, the import of virtual wastewater represents a part of the total wastewater footprint of the importing economy, as it is an indirect impact on the environment abroad. ...
The Croatian economy performs unfavorably in terms of the impact of production on wastewater discharges, which is particularly pronounced in the industrial sectors. Each unit of gross industrial value added produced in Croatia generates significantly more wastewater discharges than in most European countries with a similar level of economic development. Moreover, in 2020, only 26.9% of the total industrial wastewater discharges of the Croatian economy were treated, while 76.2% of the total industrial wastewater discharges were directly discharged into the environment. Since most of the industrial production in the Croatian economy is destined to meet the intermediate needs of other sectors, policy makers in Croatia must take into account that the level of industrial wastewater discharges is also influenced by the production level of sectors that depend on the intermediate products of wastewater-intensive industries. For this reason, we developed a wastewater extended input–output model of the Croatian economy to determine and analyze the impact of intersectoral linkages in Croatian production systems on the amount of untreated wastewater discharges. The results of the study show that wastewater flows in the Croatian economy are largely generated by the processes of production and consumption of intermediate products from the chemical and petroleum refining sectors, which also account for the largest share of the calculated wastewater footprint of total Croatian production. In light of the emerging empirical evidence, it can be concluded that targeting market-based and regulation-based measures at wastewater-intensive producers is not sufficient to reduce the relatively high level of untreated wastewater discharges in the Croatian economy. There is also a need for appropriate integrated policy measures in sectors that have a large wastewater footprint due to their established supply chains.
... Similarly, according to , Sun et al. (2021) and Hu (2019), the net transfer value is used to represent the direction of carbon transfer: ...
Globally, China ranks first in terms of total carbon dioxide emission, one-third of which is caused by carbon transfer, which is a prerequisite for carbon reduction. Studies have ignored the path comparison and influencing factors of industrial transfer and carbon transfer. This study employed the multiregional input-output (MRIO) model to investigate the evolution trend of carbon transfer in 2002, 2007, 2012, and 2017. The study compares the consistency of the path of interprovincial industrial transfer and carbon transfer. The impact of environmental regulation, industrial structure, energy intensity, and urbanization on carbon transfer is investigated using the multiscale geographically weighted regression (MGWR) model. The results demonstrate that the path of industrial transfer and carbon transfer is similar but not wholly coupled, indicating that industrial transfer is the key factor that causes carbon transfer. Environmental regulation has a negative impact on carbon transfer, and the impact on the eastern region is higher than that on the central and western regions. Urbanization has a negative impact on carbon transfer, and the degree of impact gradually decreases. The industrial structure has a significant and positive influence on carbon transfer, and the influence coefficient gradually increases. In 2002, energy intensity played a negative role in carbon transfer; however, it had a positive effect on carbon transfer in 2007, 2012, and 2017.
... Given the complexity of pro-cessing technology and the high processing cost of industrial wastewater pollution (Jabeen et al., 2015), the reduction of industrial wastewater discharge is more important from practical perspective than its treatment. Due to this, numerous governments worldwide have implemented various effective measures to reduce the discharge of industrial wastewater (Keiser et al., 2018;Sun et al., 2021). For instance, the Clean Water Act was established by the United States to improve water quality in 1972 (Mao et al., 2021). ...
Wastewater discharge is produced as a side effect of socio-economic activities and exerts severe pressure on the environment, its characteristics depend on the rate of urbanization and industrialization. We used spatial autocorrelation, environmental Kuznets curve (EKC), and logarithmic mean Divisia index (LMDI) model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116580 to 42064.96 million tons as observed from the Moran index ranging from -0.31 to 0.30. We identified five types of the EKC (monotonically decreasing, N, inverted N, U, and inverted U shape) in 18 major cities of Sichuan province. The technical effect (from -0.28 to -16.37) can reduce the discharge of industrial wastewater, while structure effect (0.05–3.83), economy effect (0.19–7.79) and population effect (from -0.08 to 0.46) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and showed a scattered distribution characteristic in Sichuan Province from 2003 to 2018. It is necessary to strengthen technical management measures to reduce industrial wastewater discharge in Sichuan province.
The massive use of pesticides has caused environmental problems, and it is urgent to reduce the use of pesticides. Pesticide use is closely related to social and economic activities, but few studies have quantified the contribution of socioeconomic factors to changes in pesticide use. Hence, based on the multiregional input–output (MRIO) model and structural decomposition analysis (SDA), this study quantified the contribution of pesticide use intensity, production structure, local consumption and distant consumption to changes in pesticide use in China from 2012 to 2017 and further analysed the effect of distant consumption on local pesticide use at the provincial and sectoral levels. The results showed that the total use of pesticides showed a downward trend during 2012-2017. Specifically, the intensity of pesticide use was an important factor for the decrease in pesticide use, resulting in a decrease of 4.9´10 ⁵ tons of pesticide use. Nevertheless, local and distant consumption were the primary factors for the increase in pesticide use, resulting in increases of 4.37×10 ⁵ and 1.21×10 ⁵ tons, respectively. More importantly, provinces with high added value of primary industry bear the risk of pesticide pollution in provinces with high per capita GDP due to distant consumption. Moreover, the agriculture and food sectors are the most important sectors affected by distant consumption. Therefore, it is necessary to clarify provincial and sectoral responsibilities for pesticide use due to distant consumption and to encourage cross-regional technical support and sectoral cooperation for pesticide reduction.
China has entered the economic transition in the post-financial crisis era, with unprecedented new features that significantly lead to a decline in its carbon emissions. However, regional disparity implies different trajectories in regional decarbonisation. Here, we construct multi-regional input–output tables (MRIO) for 2012 and 2015 and quantitatively evaluate the regional disparity in decarbonisation and the driving forces during 2012–2015. We found China's consumption-based emissions peaked in 2013, largely driven by a peak in consumption-based emissions from developing regions. Declined intensity and industrial structures are determinants due to the economic transition. The rise of the Southwest and Central regions of China have become a new feature, driving up emissions embodied in trade and have reinforced the pattern of carbon flows in the post-financial crisis period. Export-related emissions have bounced up after years of decline, attributed to soaring export volume and export structure in the Southeast and North of the country. The disparity in developing regions has become the new feature in shaping China's economy and decarbonisation.
Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China’s water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity. The impact on inadequate water quality on water scarcity is unclear. Here the authors quantify China’s present-day water scarcity and show that inadequate water quality exacerbates China’s water scarcity, which is unevenly distributed across the country.
Industrial wastewater is one of the three industrial wastes. If substandard industrial wastewater is discharged into the environment, there will be a serious impact on the environmental quality. Excessive emissions also indicate that water resources utilization is unreasonable. Therefore, it is of great significance to study the changing trends and influencing factors of industrial wastewater discharge in order to effectively conserve resources and improve the environmental quality. In this study, the spatial autocorrelation and the environmental Kuznets curve were used to study the spatial-temporal changes and characteristics of industrial wastewater discharge at the provincial scale and prefectural scale in China in 2004-2015. Then, the Logarithmic Mean Divisia Index was used to analyze the influencing factors of wastewater discharge in this period. China's total industrial wastewater discharge showed a trend of increasing at the beginning and then decreasing, and more than half provinces or cities show this trend of decoupling from economic development. Moreover, wastewater discharge was higher in the east region and lower in the west region at both the provincial scale and prefectural scale, but the aggregation degree on the prefectural scale is more obvious than that on the provincial scale. The technical effect has a general inhibitory effect on industrial wastewater discharge, but it also promoted the discharge in a few cities; the structure effect on industrial wastewater discharge has generally changed from promotion to inhibition during the study period; and economic effect and population effect were mainly to promote industrial wastewater discharge. Therefore, a few cities should accelerate technology upgrading and industrial restructuring in recent years in order to change the promoting effect, and most cities need to strengthen the implementation of economic measures and improve the residents' environmental awareness.
At times, certain areas of China suffering from water shortages. While China's government is spurring innovation and infrastructure to help head off such problems, it may be that some water conservation could help as well. It is well-known that water is embodied in traded goods-so called "virtual water trade" (VWT). In China, it seems that many water-poor areas are perversely engaged in VWT. Further, China is engaging in the global trend of fragmentation in production, even as an interregional phenomenon. Perhaps something could be learned about conserving or reducing VWT, if we knew where and how it is practiced. Given some proximate causes, perhaps viable policies could be formulated. To this end, we employ China's multiregional input-output tables straddling two periods to trace the trade of a given region's three types of goods: local final goods, local intermediate goods, and goods that shipped to other regions and countries. We find that goods traded interregionally in China in 2012 embodied 30.4% of all water used nationwide. Nationwide, water use increased substantially over 2007-2012 due to greater shipment volumes of water-intensive products. In fact, as suspected, the rise in value chain-related trade became a major contributing factor. Coastal areas tended to be net receivers of VWT from interior provinces, although reasons differed, e.g. Shanghai received more to fulfill final demand (67.8% of net inflow) and Zhejiang for value-chain related trade (40.2% of net inflow). In sum, the variety of our findings reveals an urgent need to consider trade types and water scarcity when developing water resource allocation and conservation policies.
Microbial fuel cells (MFCs) have recently achieved energy-positive wastewater treatment at pilot scale. Despite these achievements, there is still a limited understanding as to whether all wastewaters contain sufficient amounts of energy and, if so, whether MFCs can capture a sufficient amount of energy to offset electrical energy requirements in the wastewater treatment process. Currently, there are no tools or methods available that can determine whether an MFC can be energy-neutral a priori. To address this, we derived a simple relationship by setting the electrical energy requirements of a wastewater treatment facility equal to the net energy output of the MFC, such that the resulting expression describes the minimum chemical oxygen demand (COD) removal needed to achieve energy-neutral treatment. The resulting equation is simply a function of electrical energy requirements, Coulombic Efficiency, and cell voltage. This work provides the first ever quantitative method for determining if the MFCs are feasible to achieve energy-neutral treatment for a given wastewater and what level of performance is needed.
Based on the increasing pressure on the water environment, this study aims to clarify the overall status of wastewater discharge in China, including the spatio-temporal distribution characteristics of wastewater discharge and its driving factors, so as to provide reference for developing “emission reduction” strategies in China and discuss regional sustainable development and resources environment policies. We utilized the Exploratory Spatial Data Analysis (ESDA) method to analyze the characteristics of the spatio-temporal distribution of the total wastewater discharge among 31 provinces in China from 2002 to 2013. Then, we discussed about the driving factors, affected the wastewater discharge through the Logarithmic Mean Divisia Index (LMDI) method and classified those driving factors. Results indicate that: (1) the total wastewater discharge steadily increased, based on the social economic development, with an average growth rate of 5.3% per year; the domestic wastewater discharge is the main source of total wastewater discharge, and the amount of domestic wastewater discharge is larger than the industrial wastewater discharge. There are many spatial differences of wastewater discharge among provinces via the ESDA method. For example, provinces with high wastewater discharge are mainly the developed coastal provinces such as Jiangsu Province and Guangdong Province. Provinces and their surrounding areas with low wastewater discharge are mainly the undeveloped ones in Northwest China; (2) The dominant factors affecting wastewater discharge are the economy and technological advance; The secondary one is the efficiency of resource utilization, which brings about the unstable effect; population plays a less important role in wastewater discharge. The dominant driving factors affecting wastewater discharge among 31 provinces are divided into three types, including two-factor dominant type, three-factor leading type and four-factor antagonistic type. In addition, the proposals aimed at reducing the wastewater discharge are provided on the basis of these three types.
Fifteen cores were collected from a wetland and from a stream discharging treated domestic sewage effluent, and analysed for nutrients, major and trace elements to determine the long-term effect of treated wastewater discharge on a natural wetland in the central North Island, New Zealand. Spatial and temporal distribution of Zn, Cu and Pb suggests a recent input most likely related to the operation of the Turangi Wastewater Treatment Scheme and resulting discharge of treated wastewater, as well as road runoff. N and P distribution reflects the influence of effluent discharge but the data also indicate that N content is mainly controlled by the organic matter content in the sediment. Sedimentation rates determined in three of the cores using 137Cs are higher in the southern part of the wetland and are associated with high metal concentrations. The study shows that, although the discharge of both treated wastewater and road runoff has an effect on the natural wetland, the impact appears to be mainly confined to the area closest to the point of discharge of the stream into the wetland.
To present the results of a research project on 6 heavy metals (Cd, Cu, Zn, Pb, Hg, and Cr) at 30 Fadama fields scattered around Kano.
Following a reconnaissance conducted, 30 representative Fadama lands being irrigated with wastewater were selected from zones of the city under residential, industrial, commercial, and mixed but largely residential landuses. Five additional Fadama lands not being irrigated with wastewater were selected to serve as control. Using grid sampling procedure, soil samples were selected from 0-15 cm and 20-30 cm depths and analyzed for the above listed heavy metals using atomic absorption spectrophotometry. T-test was used to compare the mean values of the metals for the Fadama lands under different landuse zones with those of the control.
Analyses of the soil data collected showed that the metals were concentrated in higher amounts in the lower (20-30 cm) than the upper (0-15 cm) depths, which was an indication of downward movement of the metals in profile of the soils. In the two soil depths, Zn was generally the most abundant, followed by Cr, then Pb, Cu, and Cd while Hg was the least. The Fadama soils in areas of mixed landuses with industrial as the dominant ones maintained the highest concentrations of the various metals.
These results indicate clearly that the Fadama soils are significantly polluted by industrial and household wastewater and that there is a particular threat from Cr and Pb pollution. There is also evidence that the metals are accumulating at lower layers of the soil profile, suggesting that not only plants and soil, but even water bodies could be under the threat of heavy metal pollution in the area.
Similarities and differences between energy analysis and EMERGY analysis are discussed and highlighted using the two approaches to analyze the same systems. With particular emphasis on accounting schemes, parallel quantitative analyses of several simple model systems are performed. For the first time in the open literature EMERGY accounting procedures are given in detail. The discussion is presented in alternating sections since the authors still disagree on several fundamental issues.
The water footprint theory has provided an effective approach for evaluating the utilization of freshwater resources in agricultural production. However, there are few studies have explored the dynamic coupling relationship between water footprint and socioeconomic factors, especially from the perspective of regional ecological features. Therefore, the water footprint method was used to investigate the dynamic evolution of agricultural water consumption from 2005 to 2015 in Zhangjiakou, an extremely water-scarce city which is divided into six ecological zones (I, II, III, IV, V, and VI). Then mathematical models such as the Gini coefficient were first employed to evaluate the spatiotemporal matching characteristics of agricultural water footprint and socioeconomic factors. The results show that: (1) The agricultural water footprint increased by 1.69 × 109 m3 in Zhangjiakou, of which the animal products water footprint increased by 1.59 × 109 m3, accounting for 94%. (2) Cereals had always been the major contributors to crop water footprint, with an increasing contribution rate from 49% to 54%. Milk and egg products were the main drivers for the increasing water footprint of animal products, with a total contribution rate increased from 46% to 55%. Meanwhile, the spatial differentiation was significant. The contribution rate of the cereal water footprint was less than 50% in counties of high-altitude ecological zones I, II and IV in 2015, while it was higher than 50% in counties of low-altitude ecological zones III, V and VI. (3) The per unit area water footprint in counties of the ecological zone III was much higher than the average level, while per capita water footprint and per unit output value water footprint were far below it, indicating agricultural structure optimization requires a comprehensive consideration of multiple socioeconomic factors. This study is expected to provide policy-makers with scientific guidance that is conducive to agricultural water conservation and ecological zone planning.
Water resources are strategically important for human production and life. However, water resources are unevenly distributed in time and space. Rational use of broad water resources such as water footprint is essential for promoting regional sustainable development. This study developed an approach that quantified water footprint of Beijing, China based on input-output data of local production and living sectors and defined an indicator system to assess the dependency and vulnerability of regional water footprint network. Results indicated that water footprint of Beijing decreased from 1.89×10¹⁰ m³ in 2007 to 1.61×10¹⁰ m³ in 2012, of which the imported virtual water accounted for 33.85% in 2007 and 26.39% in 2012, respectively. The primary industry had the smallest total water footprint but the largest proportion of imported virtual water. The secondary industry had the largest total water footprint and a moderate proportion of imported virtual water. The tertiary industry had a moderate proportion of total water footprint and the smallest proportion of imported virtual water. Regions with main virtual water export to Beijing include neighboring provinces and long distance provinces. These providers exerted indirect water stress on Beijing due to their own direct water stress and industrial structure. In order to reduce the vulnerability of the water footprint network, Beijing should import virtual water-related products and services from the areas with less water stress, and at the same time, it should improve the water use efficiency of its own production and consumption. The methodology suggested in this study towards decreasing the vulnerability of the water footprint network is instructive for other regions facing water scarcity like Beijing to promote rational water resources use.
The number of input-output assessments focused on energy has grown considerably in the last years. Many of these assessments combine data from multi-regional input-output (MRIO) databases with energy extensions that completely or partially depict the different stages through which energy products are supplied or used in the economy.
The improper use of some energy extensions can lead to double accounting of some energy flows, but the frequency with which this happens and the potential impact on the results are unknown. Based on a literature review, we estimate that around a quarter of the MRIO-based energy assessments reviewed incurred into double accounting. Using the EXIOBASE MRIO database, we also analyse the effects of double accounting in the absolute values and rankings of different countries’ and products’ energy footprints.
Building on the insights provided by our analysis, we offer a set of key recommendations to MRIO users to avoid the double accounting problem in the future. Likewise, we conclude that the harmonisation of the energy data across MRIO databases led by experts could simplify the choices of the data users until the provision of official energy extensions by statistical offices becomes a widespread practice.
Grey water footprint (GWF) is an essential indicator describing the effects of aquatic pollutants on water quantity, which is significantly influenced by interregional trade. Existing studies on the impacts of interregional trade on GWF in China have deviations. That is, traditional GWF is determined by the pollutant with the highest pollutant-specific GWF, but overlooks the influences of coexisting compounds. Coexisting compounds have large influences on GWF quantification. However, the impacts of interregional trade on the improved GWF in China have not been well characterized. This study integrates the multi-regional input-output analysis and an improved GWF quantification method considering multiple pollutants, to investigate the impacts of interregional trade on the GWF in China. Compared with traditional GWF, the improved GWF of Chinese regions decreases by 19-35%. Up to 35% of China's improved GWF is related to commodities that are produced outside of regions where they are finally consumed. Beijing-Tianjin and coastal regions outsource GWF to the central and northern regions. Sectors contributing the most to GWF outsourcing include corn, cattle, swine, poultry, and other animal husbandry. This study provides more accurate region-specific and sector-specific results for policy decisions on water resource conservation in China.
Land resources do not flow directly but can be allocated as “embodied land” in goods and services during economic globalization. The term “embodied arable land” can help link local land allocation strategies to the global and national supply chains and trade activities, and suggest new lens in optimizing arable land allocation. China is facing a serious arable land shortage, especially in municipal administrative areas. Based on the nested input-output analysis (Nested IOA), this work takes Shanghai as an example, exploring the allocation of direct and embodied arable land of an urban economy within the process of economic globalization. The amount of embodied arable land associated with Shanghai economy is 6.09 Mha, broken down into local arable land use (0.20 Mha), domestic inflows (3.20 Mha) and foreign inflows (2.69 Mha). This area supports local final demand (4.32 Mha), domestic outflows (1.24 Mha) and foreign outflows (0.53 Mha). Land-related imbalances emerge in the study, namely the economy’s demand versus the city’s size, the arable land demand versus supply, and embodied arable land inflows versus outflows. Regarding the role of the urban economy in allocation of global arable land under economic globalization, on the one hand, Shanghai has intensively involved with a large amount of embodied foreign arable land resources, and has been heavy dependent on foreign embodied arable land; On the other hand, there is still large potential for Shanghai to take the opportunity of economic globalization for an optimal allocation of direct and embodied arable land. Policy suggestions on taking the opportunity of economic globalization for an optimal allocation of direct and embodied arable land are put forward.
To investigate the effectiveness of advanced treatment methods such as Electro coagulation (EC) and advanced oxidation process (AOP) in order to minimize the Colour, concentration of chemical oxygen demand and biochemical oxygen demand for the samples collected from textile dyeing waste water. Experiments carried out at lab scale model. The EC process was conducted by varying voltages such as 8 V, 10 V, 12 V, 14 V, 16 V and for duration of 60 mins each. AOP involves oxidation process in the wastewater using Fenton’s reagent (Fe²⁺/H2O2). The experiment was conducted at three different dosages such as 3 g + 30 ml, 4 g + 40 ml and 5 g + 50 ml of Fe²⁺ and H2O2. From the results obtained, the removal efficiency was determined by comparing the important parameters such as COD, BOD and Colour of treated water as well as untreated waste water. The obtained results from the treatments were in accordance with the standards given by Central Pollution Control Board (CPCB) of India for textile wastewater discharge.
China's strategy of greening industrial development aims to decouple industrial growth from industrial wastewater discharges (IWDs). This study combines decoupling analysis, decomposition analysis, and attribution analysis to support the goal. First, the decoupling analysis is employed to explore the decoupling states between industrial growth and IWDs in China, as well as across 30 provinces, from 2000 to 2015. Next, the decomposition analysis focusing on the change in industrial wastewater discharge intensity (IWDI) is performed to reveal the factors influencing the decoupling trends. Then, the attribution analysis is used to attribute the contributions of these factors to different regions. Our decoupling results indicate an increasing decoupling trend between industrial output and IWDs in China in the past 15 years. Meanwhile, there is a witnessed convergence in decoupling degrees among provinces. Decomposition results reveal that the water intensity plays the dominant role in promoting decoupling, while the wastewater discharge coefficient negatively impacts decoupling before 2005 but then exhibits a promotion effect. Regional attribution results indicate provinces in South China have exerted more efforts in both of water saving and wastewater treatment during the study period. Water scarce provinces in North China performs better in the water saving, while more developed and water rich provinces in South China provinces performs better in wastewater treatment. This paper suggests targeted policy methods at province level.
Inter-province trade of commodities and services involves not only the virtual water flows, but also the water pollution shifting which influences the water quality stress in both import and export provinces. This study estimated the production-based and consumption-based gray water footprints (GWFs) of chemical oxygen demand (COD) and ammoniacal nitrogen (NH3–N) of 30 provinces in China, and further elaborated the pollution shifting due to inter-province trade of commodities and services. The national GWF was 1586 billion m3 in 2012, mainly distributed in agriculture-dominated provinces, e.g., Guangdong, Hunan, Henan, Jiangsu, Shandong, Sichuan and Hubei. Our results also found that the national net water pollution shifting volumes were 2.8 million tons of COD and 0.2 million tons of NH3–N. Relatively wealthy provinces, such as Beijing, Shanghai and Tianjin, played significant roles in the national net pollution shifting. In accordance with the shifting of COD and NH3–N, 525 billion m3 of net GWFs were shifted from the importers to the exporters. Hebei, Shandong and Guangdong were the major outsourcing provinces of GWFs, whereas Hunan, Henan, and Heilongjiang were the major receiving provinces. We also found that most of the major water pollution receiving provinces present severe water quality stresses, particularly for Jiangsu, Henan and Anhui. Our results present the comprehensive water pollution consequences (internal and external) of daily economic activities in each province, and provide scientific instructions for inter-regional environment protection and policy making in China and far beyond.
Large amounts of wastewater discharge have emerged as a burden in the process of industrialization and urbanization. In this study, a dynamic wastewater-induced input-output model is developed to systematically analyze the related situation. The developed model is applied to Guangdong Province, China to analyze its prominent characteristics from 2002 to 2015. Combining input-output analysis, ecological network analysis and structural decomposition analysis, the developed model reveals issues of direct and indirect discharges, relationships among various discharges, and driving forces of wastewater discharges. It is uncovered that Primary Manufacturing and Advanced Manufacturing dominate the system because of significant temporal and spatial variations in wastewater discharge. In addition, Manufacturing of paper, computer and machinery and Services are the key industries responsible for large amounts of wastewater discharge and unhealthy source-discharge relationships. The largest wastewater discharge occurred in 2005 and indirect wastewater discharge is the main form. Furthermore, final demand is found to be the biggest driving force of wastewater discharge. Finally, a three-phase policy implementation system implemented in stages proposes solutions to wastewater problems.
Grey water footprint (GWF) accounting has previously been conducted at the global level using a bottom-up approach but lacking detailed industrial information. Here we applied a multi-region inputoutput approach based on the World Input-Output Database (WIOD) to quantify global GWF of 40 countries/regions with 35 economic sectors. The GWF from both the production perspective (GWFP), and the consumption perspective (GWFC) are quantified. The results show that the global GWFP/GWFC was 1507.9 km3 in 2009. Except for the “Agriculture, Hunting, Forestry and Fishing” sector, the industrial
sectors with the largest GWFC were “Food, Beverages and Tobacco”, “Construction”, “Chemicals and Chemical Products”, and “Textiles and Textile Products”. The BRIC countries (Brazil, Russia, India, China) had a larger GWFP than their GWFC, which accounted for over half of global GWFP (53.6%), and their GWFP was mainly generated from the production of domestic final demand. In contrast, the OECD29 and EU27 groups of countries i.e. the country groups consisting mainly of economically advanced nations,
had larger GWFC than their GWFP. Overall, the OECD29 and EU27 outsourced 134.8 km3 and 64.4 km3 of their grey water respectively, mostly to large newly advanced economies such as the BRIC group of countries, which, in turn, were collectively outsourcing 112 km3 of grey water. Quantitative approaches are thus suggested for development, aimed at shared responsibility for water pollutant discharge among poor exporters and wealthy consumers.
The Beijing-Tianjin-Hebei region's rapid economic development has led to a dramatic increase in its CO 2 emissions, which is closely related to various regions’ consumption habits and structures. In this paper, the decomposition analysis method based on input and output (IO-SDA) was applied to decompose the CO 2 emissions change of the Beijing-Tianjin-Hebei region from 1997 to 2012 into five driving factors: population, carbon emission efficiency, production structure, final use structure and per capita regional GDP, and then the final use structure factor was further analyzed. The results show that: (1) the population and per capita regional GDP promote the CO 2 emissions of all regions; Carbon emission efficiency is the biggest offsetting factor; The effect of final use structure changes on the growth of CO 2 emissions in Beijing and Hebei remains unchanged. The effect on Tianjin was from 0.7Mt offset to 0.8Mt promotion. (2) Urban household consumption is the most important factor offsetting CO 2 emissions in Beijing. Investment and export are the most important final use types for promoting the growth of CO 2 emissions in Tianjin and Hebei, with the contribution of 95.78% and 88.09%, respectively. (3) From the sectoral perspective: The construction sector has the greatest impact on the total capital formation of the three regions. In terms of exports, Beijing's tertiary industry has the largest offsetting effect, while Tianjin and Hebei mainly rely on the promotion of metal smelting and other manufacturing industries. Finally, some policy implications for low carbonization are proposed in the Beijing-Tianjin-Hebei region.
Haze is one of the most serious environmental problems in China, of which Beijing has been suffered from frequent haze events for years. As the major contributor of haze, PM 2.5 emission needs more investigation, especially its driving forces that is crucial for mitigation and pollution control. In this study, the main contributors of PM 2.5 emissions in Beijing were identified. By using the emission inventory and environmentally extended input–output framework, a structural decomposition model was employed to figure out the key drivers of the primary PM 2.5 emissions in Beijing. The results showed that measures to control air pollution (e.g., the Beijing Clean Air Action Plan (2013–2017)) have caused PM 2.5 emissions to decrease in recent years, indicating that emission mitigation strategies in Beijing are having preliminary success. Among all emission sources, due to large amounts of coke consumption, direct emission from residential energy consumption constitutes the largest proportion (31.05%–44.48%). Driven by fast urbanization and economic growth, high contribution of capital was invested to construction activities, which makes capital formation the largest driver of PM 2.5 emissions from consumption perspective. PM 2.5 emissions embodied in imports and exports also make a large proportion of consumption-based emission. Consumption volume and population growth are the main socioeconomic drivers to PM 2.5 emissions increase, while emission intensity and consumption patterns offset the increase of emissions. The results will be useful developing PM 2.5 emission mitigation measures and policies for Beijing and similar cities around the world.
Energy/emission intensity indicators measure the relationship between economic development and climate change. These intensity indicators are preferentially used in assessment criteria for mitigation goals in places such as China. This paper investigates the driving factors of changes in the national CO2 emission intensity and their contributions to reductions at the sector level in China from 2002 to 2012 using multiplicative structural decomposition analysis (SDA) and attribution analysis. Both Leontief and Ghosh input-output models are used in the study. The empirical results indicate: 1) the energy intensity effect is the main driver that decreases the aggregate emission intensity from both the demand and supply sides; 2) structural effects, such as the energy structure effect and domestic Ghosh structure effect, promote the increase in aggregate emission intensity principally; and 3) to a large extent, sector “smelting and pressing of metals” “manufacture of non-metallic mineral products” and “chemical industry” are the top three sectors that contribute to the negative energy intensity effect. Ultimately, several discussions and conclusions associated with the empirical results, result stability and research extensibility are presented.
This study performed an input-output structural decomposition analysis on changes in COD, ammonia nitrogen, SO2, NOx, soot and dust, industrial solid waste, and CO2 emission multipliers for 41 final products over the period 2007–2012 in China. The results show that during the examined period, emission multipliers were, in general, decreasing. The main driver of this was technical effects. The effects that made a significant contribution were concentrated in eight sectors: coal mining and washing; metals mining and quarrying; food and tobacco products; paper printing manufacturing; the chemical industry; non-metallic mineral products; metal smelting and rolling processing; and electricity, heat production, and supply. Moreover, the technical effects presented an obvious spillover. Although the contribution of the structural effects was far less than the technical ones, there were still some structural adjustments that led to significant synergistic mitigation. For example, the decrease in the direct demand of the agriculture products, electricity, and heat for food and tobacco products commonly reduced SO2, NOx, and CO2. In addition, four technical effects and most of the structural effects with high efficiency made small contributions. More than one third of the structural effects that showed obvious contributions played a positive role.
Identifying the characteristics of carbon footprint in different provinces and the inter-provincial carbon transfer is very important for establishment and operation of national carbon market in China. Based on the MRIO model, this paper developed the 2007 multi-regional input-output table with 12 provincial regions and 14 industries of China, and analyzed carbon footprint and inter-provincial carbon transfer of the 12 regions. The results show that the characteristics of carbon footprint of different provinces vary significantly because of the differences of economic development level, industrial structure, energy intensity, industrialized level and population, etc. Carbon transfer shows a tendency from the provinces with rich natural resources and heavy chemical industries to those with high economic development level and poor natural resources. Specifically, the three provinces, i.e. Hebei, Shanxi and Inner Mongolia, suffered large amount of net carbon emission transfer to other provinces. The scales of inter-provincial carbon transfer correlate negatively with distance while positively with complementarity of industry structure among different provinces. At present, China should accelerate energy structure adjustment as well as industrial structure improvement, and consolidate inter-provincial coordination on carbon mitigation to cut the cost of carbon emission reduction. Facing future national carbon emission trading system, China should comprehensively consider the characteristics of the carbon footprint of different provinces and the inter-provincial carbon transfer, scientifically define the responsibilities of each province on carbon mitigation, and allocate carbon emission quotas in a fair and reasonable manner to ensure the successful operation of the national carbon market of China.
Water pollution can be transferred either through natural water bodies or, indirectly, through economic activities. The former is a physical transfer, which has been extensively investigated and just used for controlling pollution of transboundary river basin. The latter is a virtual transfer, as shown by some studies, where it is demonstrated that the quantity of pollutants embodied in economic activities is much larger and worthy attention. However, understanding the mechanisms of virtual water pollution transfer through economic activities and relating them to domestic water resources remains a challenge. This study approaches this subject focusing on the use of the Gray Water Footprint (GWF) to account for the virtual water pollution. Based on natural background concentration, GWF is defined as the essential quantity of fresh water in order to assimilate the load of pollutants discharged into water. GWF reflects the impact of water pollution on the available quantity of water resources. GWF assessment has been tested quantifying and tracking Beijing's water pollutants emission flows embodied in economic activities. Based also on an Economic Input-Output Life Cycle assessment, we found that: 1) the material exchange between economic sectors cause the water pollution transferred virtually from down-stream industry to up-stream industry. For example, food and tobacco sector transfers 23.28 × 10⁷ m³ virtual water pollution to the agriculture sector. Consequently, the sectors which receive intermediate products from others, should share responsibility for water pollution; 2) 39.19 × 10⁷ m³ of virtual water pollution, embodied in the exports of other regions, are induced by Beijing's consumption pattern. It is suggested that measures should be introduced to reduce water pollution by integrating cross-regional production and consumption patterns.
To curb the increasing pollutant emissions that have accompanied rapid economic growth, China implemented a mandatory emissions control system since the 11th Five-Year Plan (FYP) period, and the emission reduction targets have been met and even exceeded. This article explores how China achieved its emissions reduction targets by systematically identifying the main emission reduction pathways, including both the environmental and economic factors, and evaluates the contribution of each factor using structure decomposition analysis. A study of the two key controlled pollutants, industrial sulfur dioxide (SO2) and chemical oxygen demand (COD), during the 11th FYP period showed that (i) changes in the end-of-pipe treatment and pollutant generation coefficient were the dominant contributors to emissions reduction. The power and metal smelting sectors played important roles in SO2 abatement, while the paper products and food products sectors were important in COD reduction; (ii) changes to the input coefficient increased overall emissions although there was a decrease in SO2 emissions in 2007-2010 mainly due to input structure improvements in the construction sector; (iii) the trade effect largely offset the domestic emission reduction effects, although the trade effect declined during the study period; (iv) domestic demand was the main factor increasing domestic emissions; domestic investment changes (especially in the construction sector) were the major contributor to increases in SO2 emissions, and final consumption changes (especially consumption in the food production sector) were the main contributor to the increase in COD emissions. The results yield important implications for China's pollution emissions control policies.
Higher levels of ozone in the troposphere is a severe threat to both environment and human health. Many countries are concerned about the effects that critical levels of ozone have on them. Countries pollute to satisfy their domestic and external demand (production perspective) and, at the same time, these countries also generate emissions abroad indirectly via their imports and via their domestic production (consumption perspective). Spain is one of the EU countries with the highest pollution records in the emissions of tropospheric ozone precursor gases. A multiregional input-output model (MRIO) allows us to analyze the total emissions embodied in Spanish international trade in 35 sectors within the EU area and the rest of the world. MRIO models, are commonly chosen as they provide an appropriate methodological framework for complete emissions footprint estimates at the national and supranational level The results show that the most polluting sectors involved in Spanish trade are Agriculture, Basic Metals, Coke and Refined Petroleum Production. Some policy recommendations follow these results; for example, a higher number of environmental regulations focused on the Agricultural sector, such as the introduction of codes of good practices in the use of fertilizers and the promotion of cleaner production technologies might lead to less burden to the environment.
Embodied resources and pollution in international trade have been drawing attention in environmental policies research area in the context of increased level of world economy integration. However, transfer pattern of embodied pollution of China is lack of detailed research. In this study, firstly, phenomena and modes of embodied pollution transfer across regions were analyzed from the geographic perspective. It was suggested that the primary reasons for embodied pollution transfer were regional division of labor and separation of production and consumption locations. Secondly, based on a multi-regional input-output table of 30 provinces of China in 2007, an assessment model was built to assess embodied pollution of regions and that in the trade across regions. Then, four types of industrial pollutants, namely SO2, COD, solid waste and heavy metal were selected as typical pollutants and quantified according to the model, after which the spatial pattern of embodied pollution transfer of China was clarified. The results revealed that China's mainland was a net exporter of embodied pollution due to international trade. On the other hand, embodied pollution was transferred from central and western regions to eastern region within domestic trade, while eastern China was much more developed than other regions in economy and urbanization. Actually, the burden of pollution abatement of eastern region was transferred to central and western regions through inter-regional trade. Beijing, Shanghai, Guangdong, Jiangsu and Zhejiang were main regions of inputting embodied pollution, while Hebei, Shanxi, Inner Mongolia and Guangxi were main regions of outputting embodied pollution, where the development at the expense of environmental quality would be unsustainable. The spatial pattern of embodied pollution transfer of China, which goes against regional equity, will turn regional economic differences into regional environmental differences in the future. Finally, some suggestions on pollution abatement were made accordingly based on the analysis.
China's rapidly growing economy and energy consumption are creating serious environmental problems on both local and global scales. Understanding the key drivers behind China's growing energy consumption and the associated CO(2) emissions is critical for the development of global climate policies and provides insight into how other emerging economies may develop a low emissions future. Using recently released Chinese economic input-output data and structural decomposition analysis we analyze how changes in China's technology, economic structure, urbanization, and lifestyles affect CO(2) emissions. We find that infrastructure construction and urban household consumption, both in turn driven by urbanization and lifestyle changes, have outpaced efficiency improvements in the growth Of CO(2) emissions. Net trade had a small effect on total emissions due to equal, but significant, growth in emissions from the production of exports and emissions avoided by imports. Technology and efficiency improvements have only partially offset consumption growth, but there remains considerable untapped potential to reduce emissions by improving both production and consumption systems. As China continues to rapidly develop there is an opportunity to further implement and extend policies, such as the Circular Economy, that will help China avoid the high emissions path taken by today's developed countries.
With China’s rapid economic development and urbanization process, cities are facing great challenges for tackling anthropogenic climate change. In this paper we present features, trajectories and driving forces for energy-related greenhouse gas (GHG) emissions from four Chinese mega-cities (Beijing, Tianjin, Shanghai and Chongqing) during 1995–2009. First, top-down GHG inventories of these four cities, including direct emissions (scope 1) and emissions from imported electricity (scope 2) are presented. Then, the driving forces for the GHG emission changes are uncovered by adopting a time serial LMDI decomposition analysis. Results indicate that annual GHG emission in these four cities exceeds more than 500 million tons and such an amount is still rapidly growing. GHG emissions are mainly generated from energy use in industrial sector and coal-burning thermal power plants. The growth of GHG emissions in four mega-cities during 1995–2009 is mainly due to economic activity effect, partially offset by improvements in carbon intensity. Besides, the proportion of indirect GHG emission from imported energy use (scope 2) keeps growing, implying that big cities are further dependent on energy/material supplies from neighboring regions. Therefore, a comprehensive consideration on various perspectives is needed so that different stakeholders can better understand their responsibilities on reducing total GHG emissions.
Structural decomposition techniques are widely used to break down the growth in some variable into the changes in its determinants. In this paper, we discuss the problems caused by the existence of a multitude of equivalent decomposition forms which are used to measure the contribution of a specific determinant. Although it is well known that structural decompositions are not unique, the extent of the problem and its consequences seem to have been largely neglected. In an empirical analysis for The Netherlands between 1986 and 1992, results are calculated for 24 equivalent decomposition forms. The outcomes exhibit a large degree of variability across the different forms. We also examine the two approaches that have been used predominantly in the literature. The average of the two so-called polar decompositions appears to be remarkably close to the average of the full set of 24 decompositions. The approximate decomposition with mid-point weights appears to be almost exact. Although this last alternative might seem a solution to the problem of the marked sensitivity, in fact, it only conceals the problem.
Empirical study oni nfluencing factors of regional differences in industrial wastewater discharge in China
- Li
The driving factors of China's embodied carbon emissions: a study from the perspectives of inter-provincial trade and international trade
- Pu
The analysis about change of embodied wastewater emissions of Chinese industry foreign trade
- Zhang
Evolution of spatial pattern of industrial wastewater pollution emission in China
- Shi
Research on the spatio-temporal variation of pollutant discharged from industrial wastewater in the Liaohe River Basin
- Su
Quantitative analysis on the influential factors of induastrial waste drainage
- Xie