Air pollution and health - WITCH - Revision history

Laurent Drouet: /* Air Pollution Policies */

2016-10-11T16:18:38Z

Air Pollution Policies

← Older revision		Revision as of 18:18, 11 October 2016
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	== Air Pollution Policies ==		== Air Pollution Policies ==

	Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor ''~~ef_{j,p}(t)~~'' for activity category ''j'' and for pollutant ''p''.		Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor ''ef'' for activity category ''j'' and for pollutant ''p''.

	Accordingly, the ''ef'' are defined per air pollution scenario/baseline/policy, which corresponds to different levels of control, also called End-of-Pipe (EOP), measures. The air pollution scenarios are CLE (current legislation), SLE (stringent legislation) and MFR (maximum feasible reduction). The CLE scenario corresponds to the implementation until 2030 of all the legislation already (in 2013) foreseen and/or enforced for that period; The SLE scenario foresees the implementation of 75% of the MFR scenario which corresponds to the maximal technological frontier of EOP.		Accordingly, the ''ef'' are defined per air pollution scenario/baseline/policy, which corresponds to different levels of control, also called End-of-Pipe (EOP), measures. The air pollution scenarios are CLE (current legislation), SLE (stringent legislation) and MFR (maximum feasible reduction). The CLE scenario corresponds to the implementation until 2030 of all the legislation already (in 2013) foreseen and/or enforced for that period; The SLE scenario foresees the implementation of 75% of the MFR scenario which corresponds to the maximal technological frontier of EOP.
	For the exogenous sectors the implementation of policies has to be carried out via emission pathways.		For the exogenous sectors the implementation of policies has to be carried out via emission pathways.

Laurent Drouet at 14:54, 11 October 2016

2016-10-11T14:54:50Z

← Older revision		Revision as of 16:54, 11 October 2016
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	The WITCH air pollution module relates the pollution economic activities to		The WITCH air pollution module relates the pollution economic activities to
	emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and		emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario.

			==Implementation==

			The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and
	Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.		Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.
	In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions ''E'' of pollutant ''p'' at time period ''t'' according to		In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions ''E'' of pollutant ''p'' at time period ''t'' according to
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	In WITCH we do not model all the activities that generate air pollution, therefore the non-energy related pollution is accounted for exogenously. For this non-modelled sectors the emissions are taken directly from available databases and mapped into the ([http://www.emep.int/UniDoc/node7.html SNAP sectors]), which are sector categories for reporting air pollutant levels. The emissions of the exo-sectors (sectors that are related to energy but are not accounted in the model directly, see the table in Appendix), from the EMF30 database. The non-energy sectors, such as Solvents, Waste (landfills, waste water, non-energy incineration), Agriculture waste burning on fields, Agriculture, Grassland burning and Forest burning and the emissions of ammonia follow the RCP8.5 emissions from the [http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome RCP]) database.		In WITCH we do not model all the activities that generate air pollution, therefore the non-energy related pollution is accounted for exogenously. For this non-modelled sectors the emissions are taken directly from available databases and mapped into the ([http://www.emep.int/UniDoc/node7.html SNAP sectors]), which are sector categories for reporting air pollutant levels. The emissions of the exo-sectors (sectors that are related to energy but are not accounted in the model directly, see the table in Appendix), from the EMF30 database. The non-energy sectors, such as Solvents, Waste (landfills, waste water, non-energy incineration), Agriculture waste burning on fields, Agriculture, Grassland burning and Forest burning and the emissions of ammonia follow the RCP8.5 emissions from the [http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome RCP]) database.

	# Air Pollution Policies		== Air Pollution Policies ==

	Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor ''ef_{j,p}(t)'' for activity category ''j'' and for pollutant ''p''.		Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor ''ef_{j,p}(t)'' for activity category ''j'' and for pollutant ''p''.

Laurent Drouet at 14:53, 11 October 2016

2016-10-11T14:53:00Z

← Older revision		Revision as of 16:53, 11 October 2016
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	}}		}}

	The air ~~quality~~ module relates the pollution economic activities to		The WITCH air pollution module relates the pollution economic activities to
	emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and		emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and
	Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.		Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.
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	E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)		E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)
	</math>		</math>
	where ''ef'' is the emission factor related to activity, ''A'' of sector ''j''.		where ''ef'' is the emission factor related to activity, ''A'' of sector ''j''.
	We consider the air pollutants p: carbon monoxide CO, methane CH4,		We consider the air pollutants p: carbon monoxide CO, methane CH4,
	black carbon BC, organic carbon OC, ~~sulphur~~ dioxide SO2,		black carbon BC, organic carbon OC, sulfur dioxide SO2,
	nitrogen oxides NOx, ammonia NH3 and volatile organic compounds VOC.		nitrogen oxides NOx, ammonia NH3 and volatile organic compounds VOC.

	The emission factors ''~~ef_{j,p}(t)~~'' are calculated using the ratio of emissions(E) over activities(A)		The emission factors ''ef'' are calculated using the ratio of emissions(E) over activities(A)
	provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),		provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),

Laurent Drouet at 14:49, 11 October 2016

2016-10-11T14:49:20Z

← Older revision		Revision as of 16:49, 11 October 2016
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	emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and		emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and
	Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.		Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.
	In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions ~~_E_~~ of pollutant ~~_p_~~ at time period ~~_t_~~ according to		In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions ''E'' of pollutant ''p'' at time period ''t'' according to

	<math style="font-size: 1.5em;">		<math style="font-size: 1.5em;">
	E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)		E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)
	</math>		</math>
			where ''ef'' is the emission factor related to activity, ''A'' of sector ''j''.
			We consider the air pollutants p: carbon monoxide CO, methane CH4,
			black carbon BC, organic carbon OC, sulphur dioxide SO2,
			nitrogen oxides NOx, ammonia NH3 and volatile organic compounds VOC.

	~~where $ef_{j,p}(t)$ is the emission factor related to activity, $A$ of sector $j$.~~		The emission factors ''ef_{j,p}(t)'' are calculated using the ratio of emissions(E) over activities(A)
	~~We consider the air pollutants p: carbon monoxide CO, methane CH4,~~		provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),
	~~black carbon BC, organic carbon OC, sulphur dioxide SO2,~~
	~~nitrogen oxides NOx, ammonia NH3 and volatile organic compounds VOC.~~

	The emission factors $ef_{j,p}(t)$ are calculated using the ratio of emissions(E) over activities(A) provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),

	<math style="font-size: 1.5em;">		<math style="font-size: 1.5em;">
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	</math>		</math>

	where $j$ are the WITCH sectors and $p$ is the pollutant.		where ''j'' are the WITCH sectors and ''p'' is the pollutant.

	The emission factors are then aggregated into the WITCH regions, using the mean weighted by country's level of ~~CO$_2$~~ emissions.		The emission factors are then aggregated into the WITCH regions, using the mean weighted by country's level of CO2 emissions.

	In WITCH we do not model all the activities that generate air pollution, therefore the non-energy related pollution is accounted for exogenously. For this non-modelled sectors the emissions are taken directly from available databases and mapped into the ([~~SNAP sectors](~~http://www.emep.int/UniDoc/node7.html)), which are sector categories for reporting air pollutant levels. The emissions of the exo-sectors (sectors that are related to energy but are not accounted in the model directly, see the table in Appendix), from the EMF30 database. The non-energy sectors, such as Solvents, Waste (landfills, waste water, non-energy incineration), Agriculture waste burning on fields, Agriculture, Grassland burning and Forest burning and the emissions of ammonia follow the RCP8.5 emissions from the [~~RCP](~~http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome) database.		In WITCH we do not model all the activities that generate air pollution, therefore the non-energy related pollution is accounted for exogenously. For this non-modelled sectors the emissions are taken directly from available databases and mapped into the ([http://www.emep.int/UniDoc/node7.html SNAP sectors]), which are sector categories for reporting air pollutant levels. The emissions of the exo-sectors (sectors that are related to energy but are not accounted in the model directly, see the table in Appendix), from the EMF30 database. The non-energy sectors, such as Solvents, Waste (landfills, waste water, non-energy incineration), Agriculture waste burning on fields, Agriculture, Grassland burning and Forest burning and the emissions of ammonia follow the RCP8.5 emissions from the [http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome RCP]) database.

	# Air Pollution Policies		# Air Pollution Policies

	Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor $ef_{j,p}(t)$ for activity category $j$ and for pollutant $p$.		Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor ''ef_{j,p}(t)'' for activity category ''j'' and for pollutant ''p''.

	Accordingly, the ~~$ef_{j,p}(t)$~~ are defined per air pollution scenario/baseline/policy, which corresponds to different levels of control, also called End-of-Pipe (EOP), measures. The air pollution scenarios are CLE (current legislation), SLE (stringent legislation) and MFR (maximum feasible reduction). The CLE scenario corresponds to the implementation until 2030 of all the legislation already (in 2013) foreseen and/or enforced for that period; The SLE scenario foresees the implementation of 75% of the MFR scenario which corresponds to the maximal technological frontier of EOP.		Accordingly, the ''ef'' are defined per air pollution scenario/baseline/policy, which corresponds to different levels of control, also called End-of-Pipe (EOP), measures. The air pollution scenarios are CLE (current legislation), SLE (stringent legislation) and MFR (maximum feasible reduction). The CLE scenario corresponds to the implementation until 2030 of all the legislation already (in 2013) foreseen and/or enforced for that period; The SLE scenario foresees the implementation of 75% of the MFR scenario which corresponds to the maximal technological frontier of EOP.
	For the exogenous sectors the implementation of policies has to be carried out via emission pathways.		For the exogenous sectors the implementation of policies has to be carried out via emission pathways.

Laurent Drouet at 14:43, 11 October 2016

2016-10-11T14:43:00Z

← Older revision		Revision as of 16:43, 11 October 2016
Line 5:		Line 5:

	The air quality module relates the pollution economic activities to		The air quality module relates the pollution economic activities to
	emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [~~LIMITS project](~~http://www.feem-project.net/limits/) and		emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [http://www.feem-project.net/limits LIMITS project] and
	Its emission factors have been calculated from the [~~GAINS model](~~http://gains.iiasa.ac.at/models/) in the context of the [~~EMF30](~~https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality) exercise.		Its emission factors have been calculated from the [http://gains.iiasa.ac.at/models GAINS model] in the context of the [https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality EMF30] exercise.
	In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions ~~$E$~~ of pollutant ~~$p$~~ at time period ~~$t$~~ according to		In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions _E_ of pollutant _p_ at time period _t_ according to

	$$		<math style="font-size: 1.5em;">
	E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)		E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)
	$$		</math>

	where $ef_{j,p}(t)$ is the emission factor related to activity, $A$ of sector $j$.		where $ef_{j,p}(t)$ is the emission factor related to activity, $A$ of sector $j$.
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	The emission factors $ef_{j,p}(t)$ are calculated using the ratio of emissions(E) over activities(A) provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),		The emission factors $ef_{j,p}(t)$ are calculated using the ratio of emissions(E) over activities(A) provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),

	$$		<math style="font-size: 1.5em;">
	ef_{j,p}(t) = \frac{E_{j,p,\text{GAINS}}}{A_{j,\text{GAINS}}} ,		ef_{j,p}(t) = \frac{E_{j,p,\text{GAINS}}}{A_{j,\text{GAINS}}} ,
	$$		</math>

	where $j$ are the WITCH sectors and $p$ is the pollutant.		where $j$ are the WITCH sectors and $p$ is the pollutant.

Laurent Drouet at 14:36, 11 October 2016

2016-10-11T14:36:02Z

← Older revision		Revision as of 16:36, 11 October 2016
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	\|DocumentationCategory=Air pollution and health		\|DocumentationCategory=Air pollution and health
	}}		}}

			The air quality module relates the pollution economic activities to
			emission levels of the most significant air pollutants. It allows the assessment of air pollution emissions in baseline scenarios or under a climate or pollution regulation scenario. The implementation originates from the [LIMITS project](http://www.feem-project.net/limits/) and
			Its emission factors have been calculated from the [GAINS model](http://gains.iiasa.ac.at/models/) in the context of the [EMF30](https://emf.stanford.edu/projects/emf-30-short-lived-climate-forcers-air-quality) exercise.
			In the WITCH model we use information on both fuel use and the type of electricity generation technologies employed to compute the emissions $E$ of pollutant $p$ at time period $t$ according to

			$$
			E_{p} = \sum_{j}^{ } A_{j}ef_{j,p}(t)
			$$

			where $ef_{j,p}(t)$ is the emission factor related to activity, $A$ of sector $j$.
			We consider the air pollutants p: carbon monoxide CO, methane CH4,
			black carbon BC, organic carbon OC, sulphur dioxide SO2,
			nitrogen oxides NOx, ammonia NH3 and volatile organic compounds VOC.

			The emission factors $ef_{j,p}(t)$ are calculated using the ratio of emissions(E) over activities(A) provided by GAINS, these are at a first stage aggregated over the WITCH sectors (see sector mapping on the Appendix),

			$$
			ef_{j,p}(t) = \frac{E_{j,p,\text{GAINS}}}{A_{j,\text{GAINS}}} ,
			$$

			where $j$ are the WITCH sectors and $p$ is the pollutant.

			The emission factors are then aggregated into the WITCH regions, using the mean weighted by country's level of CO$_2$ emissions.

			In WITCH we do not model all the activities that generate air pollution, therefore the non-energy related pollution is accounted for exogenously. For this non-modelled sectors the emissions are taken directly from available databases and mapped into the ([SNAP sectors](http://www.emep.int/UniDoc/node7.html)), which are sector categories for reporting air pollutant levels. The emissions of the exo-sectors (sectors that are related to energy but are not accounted in the model directly, see the table in Appendix), from the EMF30 database. The non-energy sectors, such as Solvents, Waste (landfills, waste water, non-energy incineration), Agriculture waste burning on fields, Agriculture, Grassland burning and Forest burning and the emissions of ammonia follow the RCP8.5 emissions from the [RCP](http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome) database.

			# Air Pollution Policies

			Air pollution emissions depend on two important factors, the activity level of the pollutant sector, and the emission factor of that given activity. Therefore the implementation of policies can be done via structural measures, such as changes in the model endogenous activities, or via air pollution controls. the latter is undertaken by controlling the emission factor $ef_{j,p}(t)$ for activity category $j$ and for pollutant $p$.

			Accordingly, the $ef_{j,p}(t)$ are defined per air pollution scenario/baseline/policy, which corresponds to different levels of control, also called End-of-Pipe (EOP), measures. The air pollution scenarios are CLE (current legislation), SLE (stringent legislation) and MFR (maximum feasible reduction). The CLE scenario corresponds to the implementation until 2030 of all the legislation already (in 2013) foreseen and/or enforced for that period; The SLE scenario foresees the implementation of 75% of the MFR scenario which corresponds to the maximal technological frontier of EOP.
			For the exogenous sectors the implementation of policies has to be carried out via emission pathways.

Rineke Oostenrijk: 1 revision imported

2016-08-17T10:09:45Z

1 revision imported

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