Market-based solution in China to finance the clean from the dirty.

Financial incentives play a key role in promoting renewable energy investments that can help China achieve the 'dual carbon' goal. The national emissions trading scheme (ETS) and the renewable energy portfolio standard (RPS) are two existing market-based policy instruments that can generate stable expected returns for low-carbon projects. This paper studies the interactive distribution effects of these two market-based instruments. We use the micro-level thermal power plant data to investigate the abatement effects of the national ETS, in which the details show that the existing rate-based ETS will result in higher negative impacts on power units, whose installed capacities are smaller than 400 MW. The interactive distribution effects between the two markets will occur when the permit allocation standards of the national ETS become stricter than the existing ones. Provinces in Eastern China and Northern China will face high pressure on costs in both ETS and RPS markets. When the levels of the permit allocation standards are set as 70% of the existing ones and the carbon price is assumed to be 200 yuan/ton in 2030, the annual market size of the national ETS will be nearly 100 billion yuan, and the annual market size is predicted to be 250 billion yuan. In the existing rate-based national ETS, the China Certified Emission Reduction (CCER) mechanism will have an offsetting effect, which should be taken into serious consideration during the policy-making processes in the future.

Comparative thermal assessment and emission analysis of various green biodiesel from novel feedstocks for CI engines: a sustainable approach towards emission reduction.

In order to replace conventional diesel, biodiesel from various feedstocks is being researched for diesel engines. This study explores novel biodiesel blends produced from unconventional resources such as mentha piperita (peppermint), pontederia crassipes (water hyacinth), tamarindus indica (tamarind), and trichosanthes cucumerina (snake gourd) to assess the outcomes of a diesel engine. The fuel samples are designated as MP20, PC20, TC20, and TI20, which consist of 80% biodiesel and 20% diesel. The assessment is carried out on a four-stroke, one-cylinder diesel engine that is water-cooled and set to operate at 1500 rpm with a 17.5 compression ratio under various engine loading scenarios with quarter-incremental loading from one-fourth to full loading conditions. The fuel samples are injected with 220 bar injection pressure into the combustion chamber 23° before TDC. An extensive analysis of engine parameters is performed using engine configuration, fuel characteristics, and applied boundary conditions. This comprises brake-specific energy consumption (BSEC), fuel consumption (BSFC), thermal efficiency (BTE), cylinder pressure (CP), heat release rate (HRR), particulate matter (PM), nitrogen oxide (NOx), and carbon dioxide (CO2) emissions. At 100% load, the biodiesel blends show an increase in BSFC (2.8-12.6%) and BSEC (1.1-7.1%) but a minor decrease in CP (0.9-6.9%), HRR (0.8-16.2%), and BTE (1.2-2.9%). For biodiesel blends at full engine load, the emissions of PM (8.9-21.4%), NOx (1.4-16.2%) and CO2 (2.4-7.9%) are all significantly reduced. The results emphasize the distinct benefits of biodiesel blends, demonstrating enhanced engine performance and substantial decreases in emissions, which supports the aim of providing sustainable energy solutions.

Analysis of the dynamic mechanism of trans-boundary pollution collaborative control in the Yangtze River Economic Belt.

Climate change mitigation requires simultaneous reduction of carbon emissions and air pollution. This study examines the synergy between pollution reduction and carbon reduction, identifying key variables and strategies to achieve this goal. Using a Geographical Detector model and a Coupling Degree of Coordination model, 108 cities in the Yangtze River Economic Belt (YREB) are investigated. Results show that while controlling PM2.5 has been more successful than managing carbon emissions in the YREB, synergy between pollution reduction and carbon emissions increased by an average of 7.2% from 2006 to 2019. Spatial analysis reveals higher synergy in upstream areas, indicating significant spatial diversity. The impact of pollution and emission reduction synergies is influenced by societal and environmental variables, including industry structure, technological innovation, energy structure, human capital quality, and economic basis. Synergy is amplified when natural limits align with high-quality development drivers such as technical innovation and the digital economy. Recommendations include enhancing city-to-city contact, improving energy and industrial structures, and fostering technological innovation to address regional variations in synergy levels.

Impact of extreme high temperatures on pollution emissions of enterprise: Evidence from China.

Frequently occurring extreme weather events can pose a challenge to people and production systems. Coping with extreme high temperatures requires promoting the synergy between pollution reduction and carbon reduction. Accordingly, this study examines the causal relationship between extreme high temperatures and corporate pollution emissions by using the panel data of a Chinese sample from 2000 to 2014. This study uses fixed-effects models for the analysis. Baseline results show that a unit increase in the standardized temperature will result in a 4.6% reduction in corporate pollutant emissions. The heterogeneous analysis shows that extreme high temperatures will have an obvious effect on enterprises with low financing constraints and high policy and public constraints as well as on enterprises in cities with a high level of economic development, in innovative cities, and in the eastern region. We also explore the mechanism through which extreme high temperatures reduce pollutant emissions from the two dimensions of external environmental pressure and internal environmental governance. Extreme high temperatures will prompt enterprises to improve their energy efficiency, engage in innovative production processes, adopt source-and-end governance measures, and curb their pollutant emissions while strengthening government environmental supervision. This study provides new ideas for enterprise pollution reduction and serves as an inspiration to the government in formulating environmental policies.

Assessment of Potential and Techno-Economic Performance of Solid Sorbent Direct Air Capture with CO2 Storage in Europe.

Direct air capture with CO2 storage (DACCS) is among the carbon dioxide removal (CDR) options, with the largest gap between current deployment and needed upscaling. Here, we present a geospatial analysis of the techno-economic performance of large-scale DACCS deployment in Europe using two performance indicators: CDR costs and potential. Different low-temperature heat DACCS configurations are considered, i.e., coupled to the national power grid, using waste heat and powered by curtailed electricity. Our findings reveal that the CDR potential and costs of DACCS systems are mainly driven by (i) the availability of energy sources, (ii) the location-specific climate conditions, (iii) the price and GHG intensity of electricity, and (iv) the CO2 transport distance to the nearest CO2 storage location. The results further highlight the following key findings: (i) the limited availability of waste heat, with only Sweden potentially compensating nearly 10% of national emissions through CDR, and (ii) the need for considering transport and storage of CO2 in a comprehensive techno-economic assessment of DACCS. Finally, our geospatial analysis reveals substantial differences between regions due to location-specific conditions, i.e., useful information elements and consistent insights that will contribute to assessment and feasibility studies toward effective DACCS implementation.

Industrialization Mitigates Greenhouse Gas Intensity in China's Dairy Sector yet May Prove Insufficient to Offset Emissions from Future Production Expansion.

China's dairy farming is undergoing a critical transition from extensive to industrial systems. To achieve sustainable milk production within China's dual-carbon goals, understanding the multidimensional impacts of industrialization on greenhouse gas (GHG) emissions is imperative. This study comprehensively analyzed the implications of China's dairy industrialization on GHG emissions and explored future mitigation potential. Results indicated that industrial systems exhibited lower methane but higher carbon dioxide intensities, with net GHG intensity lower than other systems. During 2002-2020, China's milk production increased by 165%, while GHG emissions increased by 105% to 50.27 Tg CO2eq, accompanying an industrialization rate increased from 16% to 75%. The industrialization progress played a mitigating effect on GHG primarily through intensification within individual production systems before 2008 and transformation between systems post-2008. However, the industrialization's effect was relatively modest compared to other socio-economic factors. By 2030, 11.8 Tg CO2eq will be triggered by predicted milk production growth, but only 0.6 Tg can be offset by system transformation. Integrating measures to improve feed, herd, and manure management on industrial farms could decouple GHG emissions from milk production and achieve a carbon peak before 2030. We suggest transforming to improved industrial systems as a necessary step toward sustainable livestock production.

[Analysis of food carbon footprint and its socio-demographic disparities in China in 2018].

OBJECTIVE: To analyze food carbon footprint and its socio-demographic disparities among adults in China. METHODS: A total of 12 777 adults aged 18 years and above from the China Health and Nutrition Survey in 2018 who have completed dietary and socio-demographic data were analyzed. The information of food intake were collected by 24 h recalls combined with the weighing of household seasonings. Food consumption was converted into energy intake by the China Food Composition Table. Carbon footprint of 26 food groups were calculated by the food carbon footprint database based on life-cycle assessment(LCA), multinomial logit model was used to analyze the association of socio-demographic factors and food carbon footprint. RESULTS: Average food carbon footprint were decreased with increasing age while increased with increasing income and education levels, and was higher among male than that among female, was higher among urban residents than that among rural residents, was higher in the south than that in the north. Multinomial logit analysis showed that compared with people aged 18-44, the likelihood of occurring high carbon footprint in 60y and above group were 29%(OR=0.71, 95%CI 0.61-0.83) lower than that occurring low carbon footprint. Women were 11%(OR=0.89, 95%CI 0.81-0.99) and 25%(OR=0.75, 95%CI 0.67-0.84) less likely to appear medium and high carbon footprint than low carbon footprint, compared with their male counterparts. In comparison to people living in cities, rural dwellers were 24%(OR=0.76, 95%CI 0.69-0.85) and 38%(OR=0.62, 95%CI 0.55-0.70) less likely to appear medium and high carbon footprint than low carbon footprint. People in the south were 3.89 times(95%CI 3.52-4.30) and 11.35 times(95%CI 10.01-12.88) more likely to occur medium and high carbon footprint than low carbon footprint, compared with people in the north. Participants were more likely to occur medium carbon footprint and high carbon footprint with the increasing income level(OR>1), and were more likely to occur high carbon footprint with the increasing education level(OR>1). CONCLUSION: The food carbon footprint of adults in China in 2018 show different socio-demographic disparities, gender, income and education level are significant factors.

A hybrid method of system dynamics and design of experiments for investigating the economic and environmental indicators of electricity industry.

Electricity plays a pivotal role in the socio-economic development of nations. However, heavy reliance on fossil fuels for electricity generation, as observed in Iran, poses significant environmental challenges. This study proposes a novel hybrid methodology that combines system dynamics modeling and Design of Experiments (DOE) to examine economic and environmental indicators within Iran's electricity sector. The system dynamics model delineates four key subsystems: consumption, production, CO2 emissions, and power trade. By integrating DOE into this framework, various economic and environmental metrics are assessed for the year 2040. Through a comprehensive analysis of variable impacts on these indicators, optimal levels are identified to achieve favorable outcomes. Notably, variables such as the allocation coefficient of export income to capacity development and electricity export price emerge as critical determinants. Due to economic, environmental, and economic-environmental indicators, the most appropriate level of allocation of export income towards capacity development is estimated at 30, 10, and 20 percent, respectively. The study recommends allocating 80 % of the capacity development budget to renewable energy sources and 20 % to thermal power plants to optimize future conditions. In business as usual, the Export CO2 emission damage to export income index will be 0.19. In implementing the proposed scenario, according to the economic-environmental index, this value will decrease and reach 1.73E-06, which indicates the improvement of electricity export from the economic-environmental dimension. This research underscores the importance of balancing economic prosperity with environmental sustainability in electricity industry planning and policy formulation.

Characterization and risk assessment of polycyclic aromatic hydrocarbons from the emission of different power generator.

Epileptic power supply in Sub-Saharan countries of Africa has warranted the use of power generators as an alternative source of power supply. Exhaust emission from these generators is associated with Polycyclic Aromatic Hydrocarbon (PAHs). Hence, this study focused on the determination of levels of PAHs in the emission of different brands of power generators used in Nigeria. Exhaust emissions of different power generators were sampled using a filter-sorbent sampling system with polyurethane foam (PUF) as an adsorbent material. Analysis of PAHs was carried out using a Gas Chromatograph coupled to a mass selective detector (GC- MS) operated on Electron Ionization (EI) mode. The results showed the ∑ PAHs range 14.91-26.0 µ g m - 3 . Bap was the most abundant of all the compounds with a concentration of 2.6 µ g m - 3 with a range of 2.08-3.07 µ g m - 3 . The Incremental Life Cancer Risk (ILCR) values of all the generator's emission sampled are higher than 10- 4 for both children and adult which indicate a high potential cancer risk from inhalation of emission from these generators while Hazard Quotient (HQ) values from all the power generating set in this study are all above 1 which indicated high associated non-carcinogenic. The study revealed the levels of PAHs associated with the emission of power generators in Nigeria.

Prognostic assessment of 18F-boronophenylalanine positron emission tomography (BPA-PET) in salvage boron neutron capture therapy for malignant brain tumors.

Background: Boron neutron capture therapy (BNCT) stands out as a propitious anti-cancer modality. 18F-boronophenylalanine positron emission tomography (BPA-PET) holds the potential to ascertain the concentration of BPA within the tumor, enabling meticulous treatment planning and outcome evaluation. However, no studies have been conducted on comparing the outcomes of those treated with BNCT to those who did not undergo this therapy. This study endeavors to analyze the correlation between BPA-PET and BNCT in the context of malignant brain tumors, and assess the survival outcomes following BNCT. Methods: A cohort study was performed on patients who underwent BPA-PET between February 2017 and April 2022 in our hospital. Patients were stratified into two groups: those subjected to BNCT (Group 1) and those not (Group 2). The tumor to normal tissue (T/N) ratio derived from BPA-PET was set at 2.5. The findings were scrutinized based on clinical follow-up. Student's t-test and Chi-squared test were employed to discern differences between the groups. A cumulative survival curve was constructed employing the Kaplan-Meier method. Differences were considered statistically significant at P<0.05. Results: In total, 116 patients with T/N ratios obtained from BPA-PET were enrolled. BNCT was administered to 58 patients, while mortality was observed in 100 patients. The median overall survival (OS) for the two groups was 8.5 and 6.0 months, respectively. The cumulative OS exhibited no significant discrepancy between the two groups, nor in their T/N ratios. Within Group 1, 44 out of 58 (75.9%) patients exhibited T/N ratios exceeding 2.5. Excluding 3 patients who expired within 3 months, 55 out of 58 patients were evaluated for response after BNCT. The objective response rate (ORR) was 30.9%. Patients achieving ORR displayed substantially higher survival rates compared to those without (median OS 13.5 vs. 8.3 months, P=0.0021), particularly when T/N ratio exceeded 2.5 (median OS 14.8 vs. 9.0 months, P=0.0199). Conclusions: BNCT does not appear indispensable for prolonging the survival of patients afflicted with malignant brain tumors. Nevertheless, it proves advantageous when ORR is attained, a condition closely linked to the values of T/N ratio derived from BPA-PET.

Evolution and driving factors of inequality in CO2 emissions from agricultural energy consumption in China.

The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China's agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya-Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China's agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

Towards sustainable development in resource-based cities: Assessing the effects of extraregional technology and investment on the low-carbon transition.

Resource-based cities (RBCs) worldwide with a single industrial structure face the double pressures of sustainable development to promote development (i.e., industrial upgrading) and mitigating carbon emissions. Although building extraregional linkages is a potential path to advance this goal, the action of these linkages still requires study since there are many contradictory conclusions in the literature. To fill this gap, the study addresses the relationship between extraregional linkages, industrial upgrading, and the low-carbon transition in RBCs from 2012 to 2019 with the help of econometric panel models with proposed variables (e.g., the coupling coordination degree of extraregional technology and investment, CCD) built from multiple new data sources. The results are as follows. First, the diversification and specialization of the local industrial structure in RBCs both reduce carbon efficiency (CE). Second, extraregional technology, on its own, does not directly enhance CE as investments do. Third, the CCD not only serves to augment CE but also acts as a mitigating factor against CE reduction during industrial diversification. Based on the above findings, distinct low-carbon transition pathways are suggested for various types of RBCs, considering their positions within the extraregional linkage network.

Green production of apples delivers environmental and economic benefits in China.

Sustainable alternative farming systems are gaining popularity worldwide because of the negative effects of conventional agriculture on global climate change and the environmental degradation caused by intensive use of synthetic inputs. The green farming system in China is an integrated production strategy that focuses on reducing chemical fertilizer use while increasing organic manure inputs. Despite their rapid growth as more sustainable systems over the past decades, green farming systems have not been systematically evaluated to date. We used apple production as a representative case to assess the sustainability of green farming systems. Across major apple-producing regions in China, green farming reduced the application of chemical fertilizer nitrogen (N) by 46.8% (from 412 to 219 kg ha-1) and increased that of manure N by 33.1% (from 171 to 227 kg ha-1) on average compared with conventional systems enhancing N use efficiency by 7.27-20.27% and reducing N losses by 8.92%-11.56%. It also slightly lowered yield by 4.34%-13.8% in four provinces. Soil fertility was improved in green orchards through increases in soil organic matter, total N, and available major nutrients. Our cradle-to-farm-gate life-cycle assessment revealed that green farming helped to mitigate greenhouse gas emissions by an average of 12.6%, potentially contributing to a reduction of 165 239 t CO2 eq annually in major apple-producing areas. In addition, green farming achieved 39.3% higher profitability ($7180 ha-1 year-1) at the farmer level. Our study demonstrates the potential of green production of apples for the development of sustainable agriculture in China. These findings advance our understanding of sustainable alternative farming systems and offer perspectives for the sustainable development of global agriculture.

Spatio-temporal evolution mechanism and dynamic simulation of nitrogen and phosphorus pollution of the Yangtze River economic Belt in China.

Excess nitrogen and phosphorus inputs are the main causes of aquatic environmental deterioration. Accurately quantifying and dynamically assessing the regional nitrogen and phosphorus pollution emission (NPPE) loads and influencing factors is crucial for local authorities to implement and formulate refined pollution reduction management strategies. In this study, we constructed a methodological framework for evaluating the spatio-temporal evolution mechanism and dynamic simulation of NPPE. We investigated the spatio-temporal evolution mechanism and influencing factors of NPPE in the Yangtze River Economic Belt (YREB) of China through the pollution load accounting model, spatial correlation analysis model, geographical detector model, back propagation neural network model, and trend analysis model. The results show that the NPPE inputs in the YREB exhibit a general trend of first rising and then falling, with uneven development among various cities in each province. Nonpoint sources are the largest source of land-based NPPE. Overall, positive spatial clustering of NPPE is observed in the cities of the YREB, and there is a certain enhancement in clustering. The GDP of the primary industry and cultivated area are important human activity factors affecting the spatial distribution of NPPE, with economic factors exerting the greatest influence on the NPPE. In the future, the change in NPPE in the YREB at the provincial level is slight, while the nitrogen pollution emissions at the municipal level will develop towards a polarization trend. Most cities in the middle and lower reaches of the YREB in 2035 will exhibit medium to high emissions. This study provides a scientific basis for the control of regional NPPE, and it is necessary to strengthen cooperation and coordination among cities in the future, jointly improve the nitrogen and phosphorus pollution tracing and control management system, and achieve regional sustainable development.

Spatiotemporal dynamics and influencing factors of CO2 emissions under regional collaboration: Evidence from the Beijing-Tianjin-Hebei region in China.

Against the backdrop of global climate change and the "dual carbon" target, cities have a significant responsibility to achieve carbon reduction targets. As a crucial urban agglomeration in northern China, effectively balancing economic growth with CO2 emission reduction to achieve high-quality economic development remains a significant challenge that the Beijing-Tianjin-Hebei region should address both presently and in the future. The objective of this study is to utilize nighttime lighting data and energy consumption information to quantify the CO2 emissions of diverse cities within the Beijing-Tianjin-Hebei region spanning from 2006 to 2020. The research aims to analyze the spatial progression patterns of CO2 emissions across these urban centers, identify key determinants and their interrelations, and delve into the underlying mechanisms pivotal for advancing carbon mitigation strategies within urban agglomerations. The results indicate that: with an exception in Beijing where CO2 emissions slightly decreased compared to 2006, CO2 emissions increased across cities in the Beijing-Tianjin-Hebei region by 2020. High-value CO2 emission areas are primarily concentrated in central of the study area, exhibiting negative spatial correlation characteristics. Based on its urban development positioning, it is imperative for the Beijing-Tianjin-Hebei urban agglomeration to formulate and implement carbon reduction strategies on innovative development, industrial upgrading, and ecological protection among other aspects towards coordinated low-carbon development.

Lymphoma: The Added Value of Radiomics, Volumes and Global Disease Assessment.

Lymphoma represents a condition that holds promise for cure with existing treatment modalities; nonetheless, the primary clinical obstacle lies in advancing therapeutic outcomes by pinpointing high-risk individuals who are unlikely to respond favorably to standard therapy. In this article, the authors will delineate the significant strides achieved in the lymphoma field, with a particular emphasis on the 3 prevalent subtypes: Hodgkin lymphoma, diffuse large B-cell lymphomas, and follicular lymphoma.

Rivers of plastic: A socio-economic and topographic approach to modeling plastic transport from catchment to sea.

Marine litter caused by discharge of mismanaged plastic waste is considered to be one of the major environmental challenges by the international society. With the annual increase of plastic production, a growing number of plastic products are being used in people's daily lives. A large number of these plastics end up as waste emitted into rivers and subsequently into oceans through the effects of downpours or wind, posing a threat to the marine ecosystem. In this study, we developed a riverine plastic transport model based on catchment topography and social-economic factors. By applying reasonable compromise on the complexity of the model, this compromised simplified process-based model has the innovative capability to estimate plastic emissions effectively under the current conditions of limited data availability for model inputs. Compared to existing models, this novel model can also resolve challenges related to the contributions of various land use types and transport stages to plastic emissions into the oceans. To further explore the applicability of our results on a global scale, certain input parameter such as the proportion of mismanaged waste is crucial for users to acquire. Here, taking the S river catchment as our study area, the tourism-driven seasonal variation of land-based plastic emissions was quantified. According to our estimation, the emission flux in S river catchment in 2020 was 68 to 280 tons. 62.4% of riverine plastics reached the ocean. Although urban areas are the predominant contributors to the total emission flux, the contributions from other land use types such as forests and cultivated areas are also unignorable. For instance, forests and cultivated areas contribute 25.7% and 6.3%, respectively, even surpassing the contributions from high tourist activity (5.8%). Stricter waste collection legislations are imperatively needed particularly in these regions.

[Multi Scenario Carbon Peak Prediction and Emission Reduction Path Analysis of Xi'an Hi-tech Zone].

The fifth session of the 13th National People's Congress proposed to be committed to promoting carbon peaking and carbon neutrality, promoting the comprehensive green and low-carbon transformation of the economy and society and achieving high-quality development. As an important scientific and technological innovation and industrial cluster in Shaanxi Province, the economic development of the Xi'an Hi-tech Zone largely relies on energy consumption, making the task of carbon reduction particularly challenging. Firstly, taking the Xi'an Hi-tech Zone as the research object, through systematic accounting of carbon emissions within the park, we analyzed the current carbon emission status of enterprises in different energy types and industries. Then, using the Kaya model, multiple independent carbon peak scenarios were set up to predict the total carbon emissions and peak time under different scenarios. Finally, based on the development characteristics of the Xi'an Hi-tech Zone, we scientifically selected corresponding carbon emission reduction paths and provided reasonable emission reduction suggestions. The results showed that the proportion of carbon emissions consumed by electricity was currently the highest, and the share was increasing yearly. Industrial carbon emissions had always been dominant, and the development of the tertiary industry was becoming increasingly prosperous. In the scenario prediction, the carbon emission factor scenario, energy intensity scenario, and economic level scenario could reach the carbon peak by 2030. Among them, the economic development level had the greatest impact on the peak and time of the future carbon peak in the Xi'an Hi-tech Zone, whereas the industrial structure scenario, energy source structure scenario, and population size scenario had no peak before 2030. The future emission reduction path mainly started from decarbonization of the power sector, stable and high-quality economic development, green upgrading of energy and industrial structure, and building a green transportation system. This can reserve more preparation time for achieving carbon neutrality and provide decision-making reference for the low-carbon development of industrial parks in China.