| Black carbon(BC)is primarily from the incomplete combustion of carbonaceous fuels(fossil and biomass),which is important for climate,environment and health.particularly,the BC emissions from residential sector(chunk coal)account for more than50%of the national total.In China 80%of the residential chunk coal is consumed for winter heating,which is one of the main reasons for the frequent occurrence of heavy pollution in winter time.The atmospheric environment in winter China is characterized by typical soot pollution.In view of the dual influence of BC's impact and control study by the uncertainty of measurement method and uncertainty of emission space-time distribution,an observation campaign was launched to study the optical properties of winter aerosols in the context of soot dominated pollution for understanding the influencing factors that affect the accuracy of the observations.Meanwhile,an analysis of the activity level data and pollutant emission factors of residential coal combustion in China was also conduncted.Significant progress has been made.Aethalometer is limited by the principle of the instrument when measuring the light absorption of BC.The measured result can only be referred to as the light attenuation coefficient(bATN)rather than the in-situ absorption coefficient(binsitu).While many studies used a number of methods to convert thebATN tobinsitu,they ignored the impacts of aerosol types and ageings on the light absorption properties of BC.In this study,two dynamic correction parameters,R and C,were constructed based on observing urban aerosols in winter.A dynamic correction algorithm was established,to correct each of the aethalometer readings.The correlation between the corrected light attenuation coefficient(bcor)andbinsitu is good(r2?0.97),which enables the aethalometer to indirectly drive the true absorption coefficient of BC(binsitu).The high primary emission and secondary formation of aerosols,coupled with varied meteorological conditions,allow northern China to alternate frequently between clean days and heavily polluted days in winter.These occurrences facilitate a detailed investigation of how significant changes in the pollution level impact the MAE and MSE,and whether current air quality improvement measures are also beneficial to the mitigation of climate change.In this study,an observation campaign was conducted in Beijing during the 2016-2017 winter season.The MAE and MSE were found to change differently with increasing pollution level.For MAE,A positive correlation between the particulate matter concentration(PM2.5)and the MAE was observed for PM2.5<100?g m-3,followed by a slowed increase in the MAE for PM2.5=100-200?g m-3;the MAE leveled off when PM2.5 concentration continues to rise.In contrast,the MSE keeps climing with increasing PM2.5.This makes current air pollution control measures possibly weaken or even eliminate the“cooling”effect of aerosols in northern China.Therefore,the future clean air measures needs to focus on reducing the proportion of BC in PM2.5 so as to prevent the risk of the"heating"effect of aerosols and achieve win-win results on air quality improvement and climate change.At this stage only average coal consumption(per household)data for the whole heating period(or whole year)are available,but little is known about how the total rural coal weight in a region could be attributed to real time(e.g.,daily)patterns,which limits the understanding of dynamic impacts of coal emissions and the adoption of timely measures against predicted haze.Considering that winter heating essentially protects against cold temperatures,coal burning strength may be related to the temperatures that people experience.A field study was organized to test the validity of this hypothesis.A system was designed to continuously monitor every instance of coal addition,and coal consumption on any given day for a whole village(WDAY)was calculated by summating all the additions.Meanwhile,a new term,composite temperature(TCOM),which incorporates a few weather-related elements,was introduced to represent cold temperatures that individuals experience.It was found that WDAY and TCOM presented opposite variations,and a negative linear correlation was observed(WDAY=-0.75TCOM+11.86,r2=0.75),revealing the feasibility of estimating coal consumption on a certain day(WDAY)based on weather data(TCOM)for a given village.An extensive form of the algorithm for any area of interest(e.g.,a district,city,or province)can be expressed as WDAY=(-0.75TCOM+11.86)?NH/834,where NH denotes the number of households in a region.This algorithm reflects the essence of winter heating(to resist cold temperatures).Through this model,the daily coal consumption in a place can be quantified according to meteorological conditions,which greatly improves the time resolution of the coal activities of the resident sector in the pollutant emission inventories,and the air quality model can accurately assess the impact of chunk coal on air quality under different conditions.To assess the impacts of chunk coal on air quality,it is necessary to know the emission factors of various chunk coals(the mass of pollutants emitted by unit mass of chunk coal)in addition to the amount of chunk coal consumed.The direct determination of chunk coal emission factors has been difficult due to the limitations in current test methods and instrumentation,and has significant uncertainties.Here,based on the optimization of the determination method,the emission factors that are reasonable for the current study were collected and statistical analysis using the Monte Carlo algorithm was conducted.The mean values and uncertainties of the emission factors of the main pollutants of the chunk coal were calculated.Combing with the"Daily coal consumption-Composite temperature"algorithm,we calculated the chunk coal BC emissions in northern China,estimated the chunk coal BC emissions from the residential sector in China,and proposed meaningful mitigation measures under current rural situation. |
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