scholarly journals Emissions from residential combustion considering end-uses and spatial constraints: Part II, emission reduction scenarios

2016 ◽  
Vol 124 ◽  
pp. 1-11 ◽  
Author(s):  
Ekbordin Winijkul ◽  
Tami C. Bond
Keyword(s):  
Emission Reduction ◽  
Spatial Constraints ◽  
Residential Combustion ◽  
End Uses

scholarly journals Comparison of source apportionment approaches and analysis of non-linearity in a real case model application

2021 ◽  
Vol 14 (7) ◽  
pp. 4731-4750
Author(s):  
Claudio A. Belis ◽  
Guido Pirovano ◽  
Maria Gabriella Villani ◽  
Giuseppe Calori ◽  
Nicola Pepe ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Emission Reduction ◽  
Road Transport ◽  
Base Case ◽  
Emission Reductions ◽  
Interaction Terms ◽  
Residential Combustion ◽  
Different Sources ◽  
Mass Concentrations ◽  
Source Allocation

Abstract. The response of particulate matter (PM) concentrations to emission reductions was analysed by assessing the results obtained with two different source apportionment approaches. The brute force (BF) method source impacts, computed at various emission reduction levels using two chemical transport models (CAMx and FARM), were compared with the contributions obtained with the tagged species (TS) approach (CAMx with the PSAT module). The study focused on the main sources of secondary inorganic aerosol precursors in the Po Valley (northern Italy): agriculture, road transport, industry and residential combustion. The interaction terms between different sources obtained from a factor decomposition analysis were used as indicators of non-linear PM10 concentration responses to individual source emission reductions. Moreover, such interaction terms were analysed in light of the free ammonia / total nitrate gas ratio to determine the relationships between the chemical regime and the non-linearity at selected sites. The impacts of the different sources were not proportional to the emission reductions, and such non-linearity was most relevant for 100 % emission reduction levels compared with smaller reduction levels (50 % and 20 %). Such differences between emission reduction levels were connected to the extent to which they modify the chemical regime in the base case. Non-linearity was mainly associated with agriculture and the interaction of this source with road transport and, to a lesser extent, with industry. Actually, the mass concentrations of PM10 allocated to agriculture by the TS and BF approaches were significantly different when a 100 % emission reduction was applied. However, in many situations the non-linearity in PM10 annual average source allocation was negligible, and the TS and BF approaches provided comparable results. PM mass concentrations attributed to the same sources by TS and BF were highly comparable in terms of spatial patterns and quantification of the source allocation for industry, transport and residential combustion. The conclusions obtained in this study for PM10 are also applicable to PM2.5.

scholarly journals Comparison of source apportionment approaches and analysis of non-linearity in a real case model application

2021 ◽  
Author(s):  
Claudio A. Belis ◽  
Guido Pirovano ◽  
Maria Gabriella Villani ◽  
Giuseppe Calori ◽  
Nicola Pepe ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Emission Reduction ◽  
Decomposition Analysis ◽  
Road Transport ◽  
Base Case ◽  
Emission Reductions ◽  
Interaction Terms ◽  
Residential Combustion ◽  
Different Sources ◽  
Source Allocation

Abstract. The response of particulate matter (PM) concentrations to emission reductions was analysed by assessing the results obtained with two different source apportionment approaches. The brute force (BF) method source impacts, computed at various emission reduction levels using two chemical transport models (CAMx and FARM), were compared with the contributions obtained with the tagged species (TS) approach (CAMx with PSAT module). The study focused on the main sources of secondary inorganic aerosol precursors in the Po Valley (Northern Italy): agriculture, road transport, industry and residential combustion. The interaction terms between different sources obtained from a factor decomposition analysis were used as indicators of non-linear PM10 concentration responses to individual source emission reductions. Moreover, such interaction terms were analysed in the light of the free ammonia/total nitrate gas ratio to determine the relationships between the chemical regime and the non-linearity at selected sites. The impacts of the different sources were not proportional to the emission reductions and such non-linearity was most relevant for 100 % emission reduction levels compared with smaller reduction levels (50 % and 20 %). Such differences between emission reduction levels were connected to the extent to which they modify the chemical regime in the base case. Non-linearity was mainly associated with agriculture and the interaction of this source with road transport and, to a lesser extent, with industry. Actually, the mass concentration of PM10 allocated to agriculture by TS and BF approaches were significantly different when a 100 % emission reduction was applied. However, in many situations the non-linearity in PM10 annual average source allocation was negligible and the TS and the BF approaches provided comparable results. PM mass concentrations attributed to the same sources by TS and BF were highly comparable in terms of spatial patterns and quantification of the source allocation for industry, transport and residential combustion. The conclusions obtained in this study for PM10 are also applicable to PM2.5.

Costs and Benefits of the Transition to Low-carbon Economyin Russia: Perspectives up to 2050

2014 ◽  
pp. 70-91 ◽  
Author(s):  
I. Bashmakov ◽  
A. Myshak
Keyword(s):  
Emission Reduction ◽  
High Probability ◽  
Ghg Emissions ◽  
Mitigation Measures ◽  
Low Carbon ◽  
Costs And Benefits ◽  
Ghg Emission ◽  
Research Groups ◽  
Emissions Mitigation ◽  
Very High

This paper investigates costs and benefits associated with low-carbon economic development pathways realization to the mid XXI century. 30 scenarios covering practically all “visions of the future” were developed by several research groups based on scenario assumptions agreed upon in advance. It is shown that with a very high probability Russian energy-related GHG emissions will reach the peak before 2050, which will be at least 11% below the 1990 emission level. The height of the peak depends on portfolio of GHG emissions mitigation measures. Efforts to keep 2050 GHG emissions 25-30% below the 1990 level bring no GDP losses. GDP impact of deep GHG emission reduction - by 50% of the 1990 level - varies from plus 4% to minus 9%. Finally, very deep GHG emission reduction - by 80% - may bring GDP losses of over 10%.

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