Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Scenario analysis on abating industrial process greenhouse gas emissions from adipic acid production in China

Adipic acid is an important petrochemical product,and its production process emits a high concentration of greenhouse gas N_2 O.This paper aims to provide quantitative references for relevant authorities to formulate greenhouse gas control roadmaps.The forecasting method of this paper is consistent with the published national inventory in terms of caliber.Based on the N_2 O abatement technical parameters of adipic acid and the production trend,this paper combines the scenario analysis and provides a measurement of comprehensive N_2 O abatement effect of the entire industry in China.Four future scenarios are assumed.The baseline scenario(BAUS) is a frozen scenario.Three emission abatement scenarios(ANAS,SNAS,and ENAS) are assumed under different strength of abatement driving parameters.The results show that China's adipic acid production process can achieve increasingly significant N_2 O emission abatement effects.Compared to the baseline scenario,by 2030,the N_2 O emission abatements of the three emission abatement scenarios can reach 207-399 kt and the emission abatement ratios can reach 32.5%-62.6%.By 2050,the N_2 O emission abatements for the three emission abatement scenarios can reach 387-540 kt and the emission abatement ratios can reach 71.4%-99.6%.

Driving factors and spatio-temporal features underlying industrial SO_(2) emissions in“2+26”in North China and extended cities

As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China between 2003 and 2017,this paper considers the dynamic spatio-temporal characteristics of industrial SO_(2) emissions in the"2+26"in North China and extended cities in North China and decomposes the determinants of industrial SO_(2) emissions into eight effects using the Generalized Divisia Index Model(GDIM).The contributions of each effect on changes in emissions are assessed on regional,provincial,and prefectural levels,as well as according to various stages.The results indicate the following.First,industrial SO2 emissions in the"2+26"cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects.Cities with high-high(HH)and low-low(LL)agglomeration patterns were concentrated in Shanxi and Henan provinces,respectively.Second,industrialization,energy consumption,and economic development were the main factors that increased industrial SO2 emissions,while technology,energy sulfur intensity,and economic sulfur intensity were the key factors that reduced them.Third,13 cities,induding Tangshan,were the most important regions where further emissions regulations need to be implemented.These cities were divided into three types and different corresponding measures for reducing their emissions are suggested.Based on the conclusions of this study,this paper puts forward some targeted policy recommendations for reducing industrial SO_(2) emissions according to different categories of cities.

Industrial carbon emissions and influencing factors in the Yangtze River Delta urban agglomeration

This paper calculates the industrial carbon emissions of the Yangtze River Delta urban agglomeration over the period 2006-2013. An empirical analysis is conducted to find out the influencing factors of industrial carbon emissions of the Yangtze River Delta urban agglomeration, using a spatial Durbin panel model. The results show that cities with larger industrial carbon emissions often enjoy low annual growth rates, while the cities with smaller ones enjoy higher annual growth rate; There exists a comparatively strong positive correlation in space in per capita carbon emission; urbanization, and total population. GDP per capita and international trade are the main influencing factors of industrial carbon emissions; There are spatial spillover effects on international trade and urbanization of neighboring cities, which have a significant impact on local industrial carbon emissions.

Power industry to reduce sulfur dioxide emissions

China has published a stricter emission standard for thermal power plants in order to help reduce the power industry's sulfur dioxide emissions by over six

Can increased economic complexity and reduced carbon emissions of the logistics industry go hand in hand?Evidence from countries along the Belt and Road

At present,the main focus of research lies in examining the connection between economic complexity and carbon emissions as a whole,but there is a scarcity of quantitative investigations on the link between the above variables within specific industries.Therefore,this study introduces economic complexity as a new variable to build a panel model within the traditional Environmental Kuznets Curve framework.Based on the data of the countries along the Belt and Road from 1998 to 2018,we used the Granger causality test to examine the causal relationship between variables,and use the Fully Modified Ordinary Least Square and Dynamic Ordinary Least Square methods to estimate the coefficients of variables.The key factor linking economic complexity and carbon emissions in the logistics industry is technology innovation Economic complexity can explain and predict the changes in carbon emissions of logistics industry more reasonably,and the relationship between them in line with the environmental kuznets curve hypothesis.Only high-income countries can increase economic complexity while reducing carbon emissions of logistics industry.Based on the empirical analysis,it is suggested that upper-middle income and lower middle-income countries can formulate relevant policies and regulations,and high-income countries can improve the relevant policies and regulations to promote the reduction of carbon emissions of the logistics industry.Studying the impact of economic complexity on carbon emissions in the logistics industry can help better predict and respond to the impact of climate change on the logistics industry.

Industrial and wildfire aerosol pollution over world heritage Lake Baikal

Lake Baikal is the biggest reservoir of fresh water with unique flora and fauna;presently it is negatively affected by climate change, water warming, industrial emissions, shipping,touristic activities, and Siberian forest fires.The assessment of air pollution-related Baikal’s ecosystem damage is an unsolved problem.Ship, based expedition exploring the Baikal atmospheric aerosol loading, was performed over the lake area in July 2018.We combine the aerosol near-water and vertical distributions over the Lake Baikal basin with meteorological observations and air mass transportation simulations.Lidar sounding of aerosol fields in the troposphere assesses the atmospheric background in the pristine areas and the pollution during fire-affected periods.Aerosol optical properties(scattering and spectral absorption) converted to the particle number size, black carbon(BC) mass, and Absorption Angstrom Exponent(AAE) provide the inside into aerosol characterization.Transport of industrial emissions from Krasnoyarsk and Irkutsk regions, and wildfire plumes from Republic of Yakutia relates the pollution sources to the increased concentrations of fine particle numbers, PM_(10) and BC mass over Southern and Northern/Central Baikal, respectively.The highest PM10 and BC are associated to the harbor and touristic areas of intensive shipping and residential biomass burning.Deposition estimates applied to aerosol data exhibit the pollution fluxes to water surface over the whole Baikal area.AAE marks the impact of coal combustion, residential biomass burning, and wildfires indicating the high pollution level of the Lake Baikal ecological system.

Efficiency Analysis of Industrial Water Treatment in China Based on Two-stage Undesirable Fixed-sum Output DEA Model

China is a country with the most water consumption, so it is lack of water resources.Industry has brought serious water pollution while driving economic development, which leads to the destruction of ecological environment. With the improvement of environmental awareness, many scholars have shifted their research direction to how to improve the ecological environment. Most studies consider the whole system as a "black box", regardless of its internal structure. Therefore, a method to identify inefficiency is necessary and some suggestions for optimization are given. In this paper,a two-stage undesirable fixed-sum output data envelopment analysis(DEA) model is proposed. The industrial chemical oxygen demand(COD) emission during 2011–2015 are adjusted, and the efficiency values are calculated by heuristic search algorithm. The efficiency of 30 provinces and cities is divided into eastern, central and western regions. The model can identify the inefficient stage in industrial system, and find the source of low efficiency in the system. The analysis shows that the efficiency of eastern region is the highest, while the overall efficiency is inclined to the pollutant treatment stage.Finally, the paper puts forward some suggestions for the low efficiency areas, which can save water while ensuring economic benefits, and provide new direction for water pollution reduction and improve the ecological environment.

Analysis of air quality characteristics of Beijing–Tianjin–Hebei and its surrounding air pollution transport channel cities in China

Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of<2.5μm(PM2.5),particulate matter with aerodynamic diameters of<10μm(PM10)and SO2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM2.5,PM10,SO2,and NO2 showed a"U"type distribution from January to December,while O3 had an"inverted U"distribution.The hourly changes in air quality revealed that peaks of PM2.5,PM10 and NO2 appeared from 8:00 to 10:00,while those for O3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.

Carbon capture for decarbonisation of energy-intensive industries:a comparative review of techno-economic feasibility of solid looping cycles

Carbon capture and storage will play a crucial role in industrial decarbonisation.However,the current literature presents a large variability in the techno-economic feasibility of CO_(2)capture technologies.Consequently,reliable pathways for carbon capture deployment in energyintensive industries are still missing.This work provides a comprehensive review of the state-of-the-art CO_(2)capture technologies for decarbonisation of the iron and steel,cement,petroleum refining,and pulp and paper industries.Amine scrubbing was shown to be the least feasible option,resulting in the average avoided CO_(2)cost of between 62.7∈t_(CO_(2))^(-1)for the pulp and paper and 104.6∈t_(CO_(2))^(-1)for the iron and steel industry.Its average equivalent energy requirement varied between 2.7(iron and steel)and 5.1MJ_(th)·kg_(CO_(2))^(-1)(cement).Retrofits of emerging calcium looping were shown to improve the overall viability of CO_(2)capture for industrial decarbonisation.Calcium looping was shown to result in the average avoided CO_(2)cost of between 32.7(iron and steel)and 42.9(cement).Its average equivalent energy requirement varied between 2.0(iron and steel)and 3.7(pulp and paper).Such performance demonstrated the superiority of calcium looping for industrial decarbonisation.Further work should focus on standardising the techno-economic assessment of technologies for industrial decarbonisation.