Assessment of the crucial factors influencing the responses of ammonia and nitrous oxide emissions to controlled release nitrogen fertilizer: A meta-analysis

Reducing ammonia(NH3) and nitrous oxide(N2O) emissions have great effects on mitigating nitrogen(N) nutrient loss and greenhouse gas emissions. Controlled release urea(CRU) can control the N release rate, which reduces reactive N loss and increases nitrogen use efficiency relative to conventional urea(CU). However, the crucial factors influencing the responses of NH3and N2O emissions to CRU relative to CU are still unclear. In this study, we evaluated the responses of NH3and N2O emissions to CRU based on collected field data with a meta-analysis. CRU reduced the NH3and N2O emissions by 32.7 and 25.0% compared with CU, respectively. According to subgroup analysis, CRU presented better mitigation of NH3and N2O emissions in soils with pH 6.5–7.5(–47.9 and –23.7%) relative to either pH<6.5(–28.5and –21.4%) or pH>7.5(–29.3 and –17.3%), and in the rice season(–34.8 and –29.1%) relative to the wheat season(–19.8 and –22.8%). The responses of NH3and N2O emissions to CRU increased from rainfed(–30.5 and –17.0%) to irrigated(–32.5 and –22.9%), and then to paddy(–34.8 and –29.1%) systems. In addition, the response of N2O emission mitigation increased with increases in soil total nitrogen(TN);however, soil TN did not significantly affect the response of NH3volatilization. The reduction in NH3emission was greater in sandy-textured soil(–57.7%) relative to loam-textured(–32.9%) and clay-textured(–32.3%) soils, whereas soil texture did not affect N2O emission. Overall, CRU was a good option for reducing the NH3and N2O emissions relative to CU in agricultural production. This analysis improves our understanding of the crucial environmental and management factors influencing the mitigation of NH3and N2O emissions under CRU application, and these site-specific factors should be considered when applying CRU to reduce reactive N loss and increase NUE.

Activity Data and Emission Factor for Forestry and Other Land Use Change Subsector to Enhance Carbon Market Policy and Action in Malawi

Activity data and emission factors are critical for estimating greenhouse gas emissions and devising effective climate change mitigation strategies. This study developed the activity data and emission factor in the Forestry and Other Land Use Change (FOLU) subsector in Malawi. The results indicate that “forestland to cropland,” and “wetland to cropland,” were the major land use changes from the year 2000 to the year 2022. The forestland steadily declined at a rate of 13,591 ha (0.5%) per annum. Similarly, grassland declined at the rate of 1651 ha (0.5%) per annum. On the other hand, cropland, wetland, and settlements steadily increased at the rate of 8228 ha (0.14%);5257 ha (0.17%);and 1941 ha (8.1%) per annum, respectively. Furthermore, the results indicate that the “grassland to forestland” changes were higher than the “forestland to grassland” changes, suggesting that forest regrowth was occurring. On the emission factor, the results interestingly indicate that there was a significant increase in carbon sequestration in the FOLU subsector from the year 2011 to 2022. Carbon sequestration increased annually by 13.66 ± 0.17 tCO2 e/ha/yr (4.6%), with an uncertainty of 2.44%. Therefore, it can be concluded that there is potential for a Carbon market in Malawi.

Investigation on emission factors of particulate matter and gaseous pollutants from crop residue burning

Emission factors of particulate matter （PM）, element carbon （EC）, organic carbon （OC）, SO2, NOx, CO, CO2, and ten ions （Na^＋, NH4^＋, K^＋, Mg^2＋, Ca^2＋, Fˉ, Clˉ, NO2ˉ, NO3ˉ, SO42ˉ） were estimated from the domestic burning of four types of commonly produced crop residues in rural China： rice straw, wheat straw, corn stover, and cotton stalk, which were collected from the representative regions across China. A combustion tower was designed to simulate the cooking conditions under which the peasants burned their crop residues in rural China, to measure the emission factors. Results showed that wheat straw had the highest emission factor for the total PM （8.75 g/kg） among the four crop residues, whereas, corn stover and wheat straw have the highest emission factor for EC （0.95 g/kg） and OC （3.46 g/kg）, respectively. Corn stover also presents as having the highest emission factors of NO, NOx, and CO2, whereas, wheat straw, rice straw, and cotton stalk had the highest emission factors of NO2, SO2, and CO, respectively. The water-soluble ions, K^＋ and Clˉ, had the highest emission factors from all the crops. Wheat straw had a relatively higher emission factor of cation species and Fˉ, Clˉ, NO2ˉ than other residues.

Real-world vehicle emission factors in Chinese metropolis city—Beijing

The dynamometer tests with different driving cycles and the real-world tests are presented. Results indicated the pollutants emission factors and fuel consumption factor with ECE15+EUDC driving cycle usually take the lowest value and with real world driving cycle occur the highest value, and different driving cycles will lead to significantly different vehicle emission factors with the same vehicle. Relative to the ECE15+EUDC driving cycle, the increasing rate of pollutant emission factors of CO, NOx and HC are -0.42—2.99, -0.32 —0.81 and -0.11—11 with FTP75 testing, 0.11—1.29, -0.77—0.64 and 0.47—10.50 with Beijing 1997 testing and 0.25—1.83, 0.09—0.75 and -0.58—1.50 with real world testing. Compared to the carburetor vehicles, the retrofit and MPI+TWC vehicles' pollution emission factors decrease with different degree. The retrofit vehicle(Santana) will reduce 4.44%—58.44% CO, -4.95%—36.79% NOx, -32.32%—33.89% HC, and -9.39%—14.29% fuel consumption, and especially that the MPI+TWC vehicle will decrease CO by 82.48%—91.76%, NOx by 44.87%—92.79%, HC by 90.00%—93.89% and fuel consumption by 5.44%—10.55%. Vehicles can cause pollution at a very high rate when operated in high power modes; however, they may not often operate in these high power modes. In analyzing vehicle emissions, it describes the fraction of time that vehicles operate in various power modes. In Beijing, vehicles spend 90% of their operation in low power modes or decelerating.

Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China’s Aviation Carbon Emissions

The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.

Impacting Factors of Elemental Mercury Re-emission across a Lab-scale Simulated Scrubber

Elemental mercury(Hg0)re-emissions from slurries and solutions were evaluated in a lab-scale simulated scrubber.Oxidized mercury(Hg2 +)standard solution was injected into the simulated scrubber at a desired rate to simulate absorbing and dissolving of Hg2 +in the flue gas across wet flue gas desulfurization(WFGD)systems. PS analytical mercury analyzer was used to continuously determine Hg0re-emission concentrations in the carrier gas from the scrubber.Sulfite ion in the slurry of CaSO3 was validated to reduce Hg 2+to Hg 0,while no Hg 0 re-emission occurred from slurries of CaSO4 and CaO.Transitional metal ions with low chemical valence such as Fe2 +,Pb 2+,Ni 2+, 2 AsO-and Cu +were used to prepare solutions with concentration levels of mmol·L-1.Reduction reaction of Hg2 +to Hg 0was observed from these solutions.Reduction capabilities for the different transitional metal ions in the solutions were:Pb2 +>Cu +>Fe 2+> 2 AsO->Ni 2+.

Estimation of SO_2 emission factors from copper smelting industry in Yunnan Province,China

Copper smelting is a significant source of SO2 emission.It is important to quantify SO2 emissions from combustion sources for regulatory and control purposes in relation to air quality.The characteristics of SO2 emissions from copper smelting industry in Yunnan Province,China,were examined.Analysis based on the present situation,material balance and measuring method were used to confirm SO2 emission factors of copper smelting industry.Results show that SO2 emission factors for Isa system,side blown-continuous converting system(SB-CC),blast furnace-continuous converting systems(B-CC) and blast furnace-converter blowing(B-C) are 11.69-18.64,62.44-101.4,19.43-37.88 and 45.48-81.03 kg/t(blister copper),respectively.The comprehensive emission factor based on all smelting plants is found to be in the range of 23 39.99 kg-SO2/t(blister copper) for Yunnan Province,China.The results are compared with those for discharge coefficients of industrial pollutants in the First National General Survey of Pollution Sources and the emission factor of the total amount of major pollutants.It is observed that there are some differences among emission factors.

The spatial distribution of commuting CO_2 emissions and the influential factors:A case study in Xi'an,China

As the transport sector is a major source of greenhouse gas emissions, the effect of urbanization on transport CO2 emissions in developing cities has become a key issue under global climate change. Examining the case of Xi'an, this paper aims to explore the spatial distribution of commuting CO2 emissions and influencing factors in the new, urban industry zones and city centers considering Xi'an's transition from a monocentric to a polycentric city in the process of urbanization. Based on household survey data from 1501 respondents, there are obvious differences in commuting CO2 emissions between new industry zones and city centers: City centers feature lower household emissions of2.86 kg CO2 per week, whereas new industry zones generally have higher household emissions of 3.20 kg CO2 per week. Contrary to previous research results, not all new industry zones have high levels of CO2emissions; with the rapid development of various types of industries, even a minimum level of household emissions of 2.53 kg CO2 per week is possible. The uneven distribution of commuting CO2 emissions is not uniformly affected by spatial parameters such as jobehousing balance, residential density, employment density, and land use diversity. Optimum combination of the spatial parameters and travel pattern along with corresponding transport infrastructure construction may be an appropriate path to reduction and control of emissions from commuting.

Life-cycle CO_2 Emissions and Their Driving Factors in Construction Sector in China

As the construction sector is a major energy consumer and thus a significant contributor of CO_2 emissions in China,it is important to consider carbon reduction in this industry.This study analyzed six life-cycle stages and calculated the life-cycle CO_2 emissions of the construction sector in 30 Chinese provincial jurisdictions to understand the disparity among them.Results show that building materials production was the key stage for carbon reduction in the construction sector,followed by the building operation stage.External variables,e.g.,economic growth,industrial structure,urbanization,price fluctuation,and marketization,were significantly correlated with the emission intensity of the construction sector.Specifically,economic growth exhibited an inverted U-shaped relation with CO_2 emissions per capita and per area during the period examined.Secondary industry and land urbanization were negatively correlated with CO_2 emission intensity indicators from the construction sector,whereas tertiary industry and urbanization were positively correlated.Price indices and marketization had negative effects on CO_2 emission intensity.The policy implications of our findings are that cleaner technologies should be encouraged for cement providers,and green purchasing rules for the construction sector should also be established.Pricing tools(e.g.,resource taxes)could help to adjust the demand for raw materials and energy.

TEMPORAL AND SPATIAL VARIATION OF EMISSIONFACTORS IN CHINA

Emission factor is a measure of pollution intensities caused by economic activities, which can be used to assess potential for pollution reduection. With the emission factors derived based on relatively few datu points or based on data collected from a specfic region, one can predict the total environmental pollution levels for the drire economy or for another region once the total leve of economic actvities of the concemed economy or region is known or prescribed. Moreover,research on emission factors can not only guide the decision-making process in choosing the best environmental protection strategy, but also be used as indicators. for the assessment and comparison of the environmentally sound development. In this paper, emission factors based on output and employment in different periods,provinces and industries are calculated, based on which temporal and spatial analyses of emission factors are carried out. Obvious declining trends of emission factors both by provinces and industries are declared, and the regional differentiation by provinces and industries is also verified.

Development of Emission Factors for Quantification of Blasting Dust at Surface

Environmental impact assessment (EIA) and environmental management plan (EMP) is a statutory requirement for execution of new mining projects or for expansion of the operating projects. For this purpose, quantification of blasting dust emission is required. This can be done by developing emission factors for blasting. The concept is similar to that of specific charge in blasting. For mining operations other than blasting, quantification of dust can be done using emis- sion factors. Emission estimation techniques are very limited for blasting. In this study, the emission factors were de- veloped by carrying out a detailed field study at one of the largest opencast coal mines of India in all four seasons. Da- ta on atmospheric and meteorological conditions were generated by installing sodar and automatic weather station at the mine site. Respirable dust samplers were installed for monitoring of the dust emitted during coal or overburden bench blasting. Emission factors for dust concentrations were developed in gram per cubic meter of rock excavated. The developed emission factors were used to estimate dust emissions for adjacent mines due to similarity in mining and meteorological conditions. Seasonal variations in moisture contents in benches, where dust was monitored, indicated the lowest emission factors in monsoon due to high moisture in the bench materials. Similar field studies were also conducted at another coalfield of India for two seasons. It was found that the emission factors are site-specific.

Impact of Greenization on the Marginal Utility of Intensity of Carbon Emissions and Factors Affecting it in China

The impact of greenization on the marginal utility of the intensity of carbon emissions in China and factors influ-encing this relationship are explored in this study.China’s level of greenization is evaluated by using an index system developed based on the comprehensive index method.The intensity of carbon emissions is determined by using the standards for the coefficients of conversion of coal equivalent and coefficients of carbon emission.The impact of greenization on the marginal utility of the intensity of carbon emissions is then evaluated by using an elastic formula and factors affecting this relationship are verified by regression analysis.The results are as fol-lows:(1)China’s level of greenization has exhibited a trend of constant increase.The intensity of carbon emissions has followed a continual downward trend while the impact of greenization on the marginal utility of the intensity of these emissions has been declining.(2)Urbanization as well as scientific and technological developments have slowed the reduction in the marginal utility of the intensity of carbon emissions,whereas the structure of energy consumption has expedited it under the diminishing impact of greenization.The standard of living of the popu-lation,intensity of environmental regulation,and environmental quality have had different influences under dif-ferent conditions.

Spatial network structure of transportation carbon emission efficiency in China and its influencing factors

Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region.Based on the ideal point cross-efficiency(IPCE)model,the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors.The results obtained showed the following outcomes.(1)During the study period,China’s provincial TCEE formed a complex and multithreaded network association relationship,but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west.(2)The correlation of China’s TCEE formed a block segmentation based on the regional boundaries,and its factional structure was relatively obvious.The eastern region was closely connected with the central region,and generally connected with the western and northeastern regions.The central region was mainly connected with the eastern and western regions,and relatively less connected with the northeastern region.Besides,the northeastern region was weakly connected with the western region.(3)Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin,and other developed provinces were in the core leading position in the TCEE network,which significantly impacted the spatial correlation of TCEE.However,Heilongjiang,Jilin,Xinjiang,Qinghai,and other remote provinces in the northeast and northwest were at the absolute edge of the network,which weakly impacted the spatial correlation of TCEE.(4)Provincial distance,economic development-level difference,transportation intensity difference,and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE.In contrast,the energy-saving technology level difference had a significant positive impact on it.The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant;their response mechanism and effects need to be improved and enhanced.

N_2O emission factors of nitric acid production in China from CDM projects

Industrial production process including nitric acid production is an important greenhouse gas emission source. Although IPCC guidelines have given calculation methods and emission factors for N2O emission from nitric acid production, emission factors of nitric acid production in China are not given. And it can be seen from the comparison of the guidelines and registered CDM projects in China that the N2O emission factors given in the IPCC guidelines and actual N2O emission from nitric acid production in China differ greatly while measured N2O emission data is not available, so determination of emission factors for N2O emission from nitric acid production is an important basic research for N2O emission calculation in China. The method that calculate N2O emission factors from nitric acid production in China is studied with baseline emission factors based on actual measurement of registered CDM projects and the calculated emission factor is compared with that given in the IPCC guidelines in the text.

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.

Low Carbon Beijing:Research on the Influencing Factors of Carbon Emission Trading Price

The international community has taken extensive actions to achieve carbon neutrality and sustainable development with the intensification of global warming and climate change.China has also carried out a long-term layout,setting the goal of achieving a carbon peak by 2030 and carbon neutrality by 2060.In 2021,with the official launch of a unified national carbon emissions trading market,China’s nationwide carbon emissions trading kicked off.Carbon emission trading is an important policy tool for China’s carbon peak and carbon-neutral action and an essential part of the country’s promotion of a comprehensive green transformation of the economy and society.This study uses a VAR(Vector Autoregressive)model to analyze the influencing factors of the Beijing carbon emissions trading price from January 2014 to December 2019.The study found that coal prices have the most significant impact on Beijing’s carbon emissions trading prices.Oil prices,industrial development indexes,and AQI(Air Quality Index)impacted Beijing’s carbon emissions trading prices.In contrast,natural gas prices and economic indexes have the most negligible impact.These findings will help decision-makers determine a reasonable price for carbon emissions trading and contribute to the market’s healthy development.

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.

Study on Carbon Emission Driving Factors and Low-carbon Policy of Transportation Industry in Henan Province

The transportation industry is the basic industry of national economic development. At the same time, it is the only industry in China that has continuously increased CO2 emissions, and the high energy consumption problems have not been solved. Henan province, as a major energy consumption province, it is urgent to improve the supply quality of transportation industry. The paper uses the IPCC calculation method for carbon emission to calculate the CO2 emissions of transportation industry in Henan province from 2004 to 2014. Then, this paper uses the LMDI method to decompose the CO2 emission in the transportation industry and give the proposal to reduce the CO2 emission according to the CO2 emission drivers.

Greenhouse gas emission analysis and measurement for urban rail transit: A review of research progress and prospects

Rail transit plays a key role in mitigating transportation system carbon emissions.Accurate measurement of urban rail transit carbon emission can help quantify the contribution of urban rail transit towards urban transportation carbon emission reduction.Since the whole life cycle of urban rail transit carbon emission measurement involves a wide range of aspects,a systematic framework model is required for analysis.This research reviews the existing studies on carbon emission of urban rail transit.First,the characteristics of urban rail transit carbon emission were determined and the complexity of carbon emission measurement was analyzed.Then,the urban rail transit carbon emission measurement models were compared and analyzed in terms of the selection of research boundaries,the types of greenhouse gas(GHG)emissions calculation,and the accuracy of the measurement.Following that,an intelligent station was introduced to analyze the practical application of digital collaboration technology and energy-saving and carbon-reducing system platforms for rail transit.Finally,the urgent problems and future research directions at this stage were discussed.This research presents the necessity of establishing a dynamic carbon emission factor library and the important development trend of system integration of carbon emission measurement and digital system technology.